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About FullStack FullStack is your AI-native engineering partner, built to turn AI capability into certainty. Most companies can demo AI; few can get it to production and prove what it produced. We close that gap with three capabilities, AI built into your products from the start, elite vetted talent who apply it, and transparent execution that shows value every step of the way. With now over 600 customers in North America, FullStack is one integrated partner for all your AI engineering needs. With FullStack, you move forward with confidence. We're Most Proud Of Offering life-changing career opportunities to talented software professionals across the Americas. Building highly-skilled software development teams for hundreds of the world's greatest companies. Having delivered hundreds of successful custom software solutions, which have positively impacted the lives and careers of millions of users. Our 4.1-star rating on GlassDoor. Our client Net Promoter Score of 68, twice the industry average. The Position We're Looking To Hire a Senior Machine Learning Engineer (Traditional ML & Financial Data) To Join Our Team. You'll Work With Our Incredible Clients In One Of Two Ways Team Augmentation: You will integrate yourself directly into our client's team and work alongside their existing designers and engineers on a daily basis. Design & Build: You will work on a FullStack product team to build and deliver a product to our clients. What We're Looking For 5+ years of professional experience in software development, Data Science, or Machine Learning Engineering. Advanced English is required. Successful completion of a four-year college degree is required. Strong expertise in traditional machine learning algorithms and statistical modeling, with a focus on non-LLM and non-Generative AI approaches. Hands-on experience designing, developing, training, and optimizing machine learning models for production use. Strong proficiency in data exploration, preprocessing, feature engineering, and model training using complex datasets. Demonstrated experience developing and optimizing anomaly detection algorithms to identify irregularities, patterns, and outliers in data. Strong Python skills and experience with relevant machine learning and data science libraries. Experience analyzing financial, payroll, or other structured business datasets is highly preferred. Proactive, ownership-driven mindset with strong analytical and problem-solving skills, capable of translating complex data into reliable machine learning solutions. Ability to work through new and difficult issues and contribute to libraries as needed. Ability to create and maintain continuous integration and delivery of applications. Forensic attention to detail. A positive mindset and a can-do attitude. Experience working on Agile/Scrum teams. Meaningful experience working on large, complex systems. Ability to take extreme ownership over your work. Every day is a challenge to ensure you are performing to the expectations you and your team have agreed upon. Ability to identify with the goals of FullStack's clients, and dedicate yourself to delivering on the commitments you and your team make to them. Nice To Have We're Seeking Engineers Who Are AI-enthusiastic In Their Workflow. Professional Experience Or Personal Project Work With The Following Is a Significant Plus Cursor, Windsurf, or Google Antigravity. Claude Code, Gemini CLI, Codex, or Copilot CLI. Work Authorization Requirements Applicants must be currently authorized to work in the United States on a full-time basis. FullStack will not sponsor applicants for work visas now or in the future. What We Offer Competitive Salary. Paid Time Off (vacation, sick leave, parental leave, and holidays). 100% remote work. The ability to work with leading startups and Fortune 500 companies. Health, dental, and vision insurance. 401(k) w/ 4% match. Ample opportunity for career advancement. Continuing education opportunities. FullStack is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. Learn more about our Applicants Privacy Notice.

About NewsBreak Local life runs on local information. What happened down the street? Who can fix this? Where should we go tonight? NewsBreak started in 2015 to answer these questions, and today more than 40 million people a month rely on us to follow what's going on in their zip code. Three platforms with one vision: powering local life. Led by founder and CEO Jeff Zheng, NewsBreak is our local life and news platform; Nearby AI connects people with local businesses; and NDot AI helps publishers and creators grow and earn. Building for the long term. A $115 million Series C made us a unicorn in 2021, and we keep investing in our people. We're Great Place to Work® certified and named to Fast Company 's Best Workplaces for Innovators (2025) and Fortune 's Best Workplaces in the Bay Area™ (2026). Everyone makes an impact. Whether you write code, shape products, tell our story, or run the business, we want people who own projects end to end, stay curious, and speak up. Join us. Learn more at: NewsBreak, Nearby AI, NDot AI About The Role We are looking for a Machine Learning Engineer to build intelligent systems that connect consumers with relevant local information, businesses, and services. You will work across areas such as search, recommendation, ranking, retrieval, user-intent understanding, personalization, and marketplace matching. Depending on your background and interests, you may focus on understanding consumer demand, improving search and recommendation relevance, or building models that more effectively match users with local supply. This is a hands-on role with the opportunity to take machine learning solutions from problem definition and experimentation through production deployment and iteration. We welcome candidates across a range of experience levels, and the scope and level of the role will be calibrated based on the candidate's experience. What You'll Do Build and improve machine learning models for search, recommendation, ranking, retrieval, matching, and personalization. Develop systems that understand user queries, behaviors, preferences, and context. Apply embeddings, natural language processing, large language models, and modern retrieval techniques to connect consumer demand with relevant local content, businesses, or services. Build and optimize end-to-end ML pipelines, from data preparation and model training to online serving and monitoring. Partner with product, engineering, and data teams to define problems, identify opportunities, and translate business needs into scalable ML solutions. Design and analyze online and offline experiments to measure model quality and product impact. Improve key product outcomes such as relevance, engagement, conversion, retention, and marketplace efficiency. Explore new ML and LLM techniques and bring them into production where they can deliver measurable value. What We're Looking For Experience building machine learning, data mining, search, recommendation, ranking, NLP, or related systems through academic projects, internships, or industry work. Strong programming skills in Python, Java, C++, or another relevant language. Solid understanding of machine learning fundamentals, data structures, algorithms, and statistical analysis. Experience with one or more of the following: Search, retrieval, or learning-to-rank Recommendation or personalization Query understanding, intent classification, or NLP Embeddings, semantic search, or large language models Matching, marketplace optimization, or dispatch Ability to work with large-scale or complex datasets and translate ambiguous problems into practical solutions. Strong collaboration and communication skills. Interest in building production systems that serve real users and deliver measurable product impact. Nice to Have Experience deploying and maintaining machine learning models in production. Experience with experimentation, including A/B testing, causal analysis, or marketplace experiments. Familiarity with deep learning frameworks and ML infrastructure, such as PyTorch, TensorFlow, Spark, Kubernetes, or feature and model-serving platforms. Experience building taxonomies, user-interest representations, knowledge graphs, or behavioral models. Experience applying LLMs to search, recommendation, classification, or information retrieval. Background in local search, local services, maps, commerce, marketplaces, delivery, mobility, or location-based products. Experience at a consumer internet, search, recommendation, advertising, e-commerce, or marketplace company. Annual Base Pay Range $190,000 - $300,000 The US base salary range for this full-time position will vary based on job-related skills, level, experience, geographic location, and relevant education or training. At NewsBreak, we design our overall rewards package to attract top talent. Depending on the position and level, the role may also be eligible for a discretionary bonus and equity. Your recruiter can share more details during the hiring process. The US base salary range for this full-time position is listed below. Pay may vary based on a number of factors including job-related skills, level, experience, geographic location and relevant education or training. At NewsBreak, we design our overall rewards package to attract top talents. Depending on the position, the role may also be eligible for discretionary bonus and options. Your recruiter can share more details during the hiring process. Annual Base Pay Range $190,000 - $300,000 USD CPRA Privacy Notice for California Candidates

The Company PayPal has been revolutionizing commerce globally for more than 25 years. Creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure, PayPal empowers consumers and businesses in approximately 200 markets to join and thrive in the global economy. We operate a global, two-sided network at scale that connects hundreds of millions of merchants and consumers. We help merchants and consumers connect, transact, and complete payments, whether they are online or in person. PayPal is more than a connection to third-party payment networks. We provide proprietary payment solutions accepted by merchants that enable the completion of payments on our platform on behalf of our customers. We offer our customers the flexibility to use their accounts to purchase and receive payments for goods and services, as well as the ability to transfer and withdraw funds. We enable consumers to exchange funds more safely with merchants using a variety of funding sources, which may include a bank account, a PayPal or Venmo account balance, PayPal and Venmo branded credit products, a credit card, a debit card, certain cryptocurrencies, or other stored value products such as gift cards, and eligible credit card rewards. Our PayPal, Venmo, and Xoom products also make it safer and simpler for friends and family to transfer funds to each other. We offer merchants an end-to-end payments solution that provides authorization and settlement capabilities, as well as instant access to funds and payouts. We also help merchants connect with their customers, process exchanges and returns, and manage risk. We enable consumers to engage in cross-border shopping and merchants to extend their global reach while reducing the complexity and friction involved in enabling cross-border trade. Our beliefs are the foundation for how we conduct business every day. We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness. Together, our values ensure that we work together as one global team with our customers at the center of everything we do – and they push us to ensure we take care of ourselves, each other, and our communities. Job Summary: This job will lead the design, development, and implementation of advanced machine learning models and algorithms to solve complex problems. You will work closely with data scientists, software engineers, and product teams to enhance services through innovative AI/ML solutions. Your role will involve building scalable ML pipelines, ensuring data quality, and deploying models into production environments to drive business insights and improve customer experiences. Job Description: Essential Responsibilities: Lead the development and optimization of advanced machine learning models. Oversee the preprocessing and analysis of large datasets. Deploy and maintain ML solutions in production environments. Collaborate with cross-functional teams to integrate ML models into products and services. Monitor and evaluate the performance of deployed models, making necessary adjustments. Minimum Qualifications: 5+ years relevant experience and a Bachelor's degree OR Any equivalent combination of education and experience. Extensive experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn. Expertise in cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment. Additional Responsibilities & Preferred Qualifications: Subsidiary: PayPal Travel Percent: 0 The base pay for this role will depend on where you work and the relevant experience and expertise you bring. The expected range of pay for this role by location is: Primary Location : Pay Range: San Jose, California: ($196,500.00 - $291,500.00 Annually) Additional Location(s) : Pay Range: No other locations are assigned to this requisition currently. Additional compensation for this role may include an annual performance bonus, equity, or other incentive compensation, as applicable. PayPal does not charge candidates any fees for courses, applications, resume reviews, interviews, background checks, or onboarding. When making an application directly, we will never ask you to share passwords, one-time passcodes (OTP), or verification codes. Any such request is a red flag and likely part of a scam. All communication regarding your application will come from official PayPal email domains. If you suspect fraudulent activity, please report it immediately. To learn more about how to identify and avoid recruitment fraud please visit https://careers.pypl.com/contact-us. For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations. Our Benefits: At PayPal, we're committed to building an equitable and inclusive global economy. And we can't do this without our most important asset-you. That's why we offer comprehensive, choice-based programs, to support all aspects of personal wellbeing—physical, emotional, and financial—delivering meaningful value where it matters most. We strive to create a flexible, balanced work culture with a holistic approach to benefits, including generous paid time off, healthcare coverage for you and your family, and resources to create financial security and support your mental health. Who We Are: Click Here to learn more about our culture and community. Commitment to Diversity and Inclusion PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at paypalglobaltalentacquisition@paypal.com. Belonging at PayPal: Our employees are central to advancing our mission, and we strive to create an environment where everyone can do their best work with a sense of purpose and belonging. Belonging at PayPal means creating a workplace with a sense of acceptance and security where all employees feel included and valued. We are proud to have a diverse workforce reflective of the merchants, consumers, and communities that we serve, and we continue to take tangible actions to cultivate inclusivity and belonging at PayPal. Any general requests for consideration of your skills, please Join our Talent Community. We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don't hesitate to apply.

← Back to all positions AI/ML Engineer Active 📍 Hybrid - San Francisco🏢 AI & Research⏱ Full-time💼 3+ years📅 Posted: 2025-01-20⏳ Closes: 2025-03-20 As an AI/ML Engineer, you will design, train, and deploy machine learning models at scale. You'll work on NLP, computer vision, and recommendation systems that directly impact millions of users. 🎯Responsibilities Design and implement ML pipelines for training and inference Develop NLP and computer vision models Optimize model performance and reduce latency Collaborate with data engineers on data pipelines Stay current with the latest AI research and apply findings ✅Requirements 3+ years of experience in ML/AI engineering Proficiency in Python, PyTorch or TensorFlow Experience with LLMs and transformer architectures Strong understanding of MLOps and model deployment MS or PhD in Computer Science, ML, or related field preferred ⭐Nice to Have Published research papers Experience with RAG systems Familiarity with cloud platforms (AWS, GCP) 🎁Benefits Competitive salary Flexible hybrid work Conference and research budget Apply for this Position 👤 Personal Information Full Name Email Address Phone Number 🇺🇸 +1🇨🇦 +1🇮🇳 +91 GitHub Profile 💼 Professional Details Current Company Current Role / Title Years of ExperienceSelect experience0 – 1 year1 – 3 years3 – 5 years5 – 8 years Expected Salary (Annual) Notice PeriodSelect notice periodImmediately available1 month2 monthsMore than 2 months When Can You Start? How Did You Hear About Us?Select sourceLinkedInGitHubTwitter / XEmployee ReferralJob Board (Indeed, Naukri, etc.)Company WebsiteGoogle SearchOther 📄 Resume / CV 📤 Click to upload your resume PDF, DOC, DOCX — Max 5MB 💡 Tell Us More About You Why are you interested in this role? 0 / 2000 What makes you a good fit for this position?* 0 / 2000 Additional Cover Letter (Optional) 0 / 5000 By submitting this application, you agree to our privacy policy and consent to the processing of your personal data for recruitment purposes.

EvenUp is on a mission to close the justice gap using technology and AI. We empower personal injury lawyers and victims to get the justice they deserve. Our products enable law firms to secure faster settlements, higher payouts, and better outcomes for victims injured through no fault of their own in vehicle collisions, accidents, natural disasters, and more. We are one of the fastest-growing vertical SaaS companies in history, and we are just getting started. EvenUp is backed by top VCs, including Bessemer Venture Partners, Bain Capital Ventures, SignalFire, and Lightspeed. We are looking to expand our team with talented, driven, and collaborative individuals who seek to have a lasting impact. Learn more at www.evenuplaw.com. Machine Learning Engineer We're looking for a Machine Learning Engineer to join our ML team at EvenUp. You'll develop and deploy models that power Piai™, our proprietary claims-intelligence platform, with a focus on machine learning, natural-language processing, and generative AI. Working alongside senior ML engineers, data scientists, and legal subject-matter experts, you'll turn raw legal and medical data into production-ready models that directly improve outcomes for personal-injury clients. What You'll Do Explore, implement, and benchmark ML, NLP, and generative AI methods - including LLM fine-tuning, retrieval-augmented generation, and document understanding. Clean, annotate, and transform structured and unstructured case data, and build reusable datasets and data loaders. Design experiments, run A/B tests, analyze results, and communicate findings to product and engineering teams. Help integrate models into our production systems, partnering with ML platform engineers on testing, monitoring, and scaling. Pair with product managers, legal analysts, and software engineers to translate real problems into ML solutions and measurable improvements. Stay current with research in LLMs, representation learning, and prompt engineering, and share what you learn with the team. What You Bring B.S., M.S., or Ph.D. in Computer Science, Machine Learning, Data Science, Statistics, Computational Linguistics, or a related field. Solid grounding in ML fundamentals - supervised and unsupervised learning, evaluation metrics, overfitting and regularization. Hands-on experience with NLP or generative AI techniques - transformers, embeddings, sequence-to-sequence models, or LLMs. Proficiency in Python and ML/NLP libraries such as PyTorch, TensorFlow, Hugging Face, or spaCy. Familiarity with SQL and basic data engineering concepts - ETL, versioned datasets, notebooks. Strong analytical thinking, clear communication, and eagerness to learn and iterate quickly in a fast-moving startup. Ability to work hybrid (3 days your choice) in our San Francisco or Toronto, Canada office. Nice to Have Exposure to cloud platforms (AWS, GCP). Experience with experiment-tracking tools (Weights & Biases, Gemini Enterprise Agent Platform, MLflow). Familiarity with containerized deployment (Docker, Kubernetes). Experience in a high-growth startup environment. Benefits & Perks: As part of our total rewards package, we offer attractive benefits and perks to our employees, including: Choice of medical, dental, and vision insurance plans for you and your family. Additional insurance coverage options for life, accident, or critical illness. Flexible paid time off, sick leave, short-term and long-term disability. 10 US observed holidays, and Canadian statutory holidays by province. A home office stipend. 401(k) for US-based employees and RRSP for Canada-based employees. Paid parental leave. A local in-person meet-up program. Hubs in San Francisco and Toronto. (Please note the above benefits & perks are for full-time employees) Notice to Candidates: To ensure fairness and proper consideration, we do not accept resumes or expressions of interest via email or social media messages. If you're interested in a role, please submit your application directly through our careers page . Please note that EvenUp may use AI notetakers and other recording devices in the recruiting process. If you interview with us, with your consent, we may record your conversations and summarize them into notes for internal use. Recording is optional, and declining will not affect your candidacy. EvenUp is an equal opportunity employer. We are committed to diversity and inclusion in our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Compensation Range: $130K - $205K

The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Blend to Discover Weekly, we're behind some of Spotify's most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you'll keep millions of users listening by making great recommendations to each and every one of them. The Surfaces Podcasts team owns podcast recommendations across some of Spotify's most visible surfaces, including Home and the Now Playing view. We build and improve the recommendation systems that help listeners discover their next favorite show or episode while helping creators reach the right audiences. As a Staff Machine Learning Engineer, you'll help shape the future of personalized discovery and engagement at Spotify. You'll work at the intersection of recommendation systems, large language models, and production-scale machine learning infrastructure to build experiences for listeners at global scale. You'll take models from research to production, help set technical direction in ambiguous problem spaces, and solve complex personalization challenges across Spotify. What You'll Do Own and improve the machine learning models and systems that power the Home feed, including the Shortcuts experience. Design, build, and ship personalized recommendations that serve millions of Spotify listeners globally. Build content recommendation systems for emerging agentic and AI-powered user experiences. Train, fine-tune, evaluate, and optimize large language models using techniques such as supervised fine-tuning (SFT), distillation, and parameter-efficient training approaches. Partner closely with Product Managers, Engineers, Data Scientists, and Designers to define and execute experimentation strategies. Drive A/B testing, monitoring, model evaluation, and continuous optimization of recommendation quality, reliability, and cost efficiency. Improve ML platform capabilities, data pipelines, and production systems that support personalization at Spotify scale. Drive technical direction in ambiguous problem spaces and contribute to the long-term architecture of our personalization systems. Mentor and support other Machine Learning Engineers, sharing knowledge and helping strengthen engineering practices across the team. Who You Are You have deep experience building and deploying machine learning systems in production environments. You have deep experience with recommendation systems, ranking models, personalization, or large-scale content discovery platforms. You are proficient in Python and have hands-on experience building machine learning systems with PyTorch. You have experience with large language model training, fine-tuning, evaluation, and optimization techniques, including SFT, distillation, and LoRA. You have worked with large-scale inference systems and understand the challenges of latency, reliability, and cost optimization. You care about creating high-quality user experiences through thoughtful applications of machine learning. You communicate effectively with technical and non-technical partners and can influence technical decisions beyond your immediate team. You know how to design, execute, and interpret online experiments and A/B tests to improve user outcomes. You have experience operating distributed machine learning workloads using technologies such as Ray, FSDP, HSDP, or similar frameworks. You have experience building and maintaining data pipelines and orchestration workflows using technologies such as Flyte, Airflow, BigQuery, and cloud-based storage platforms. Where You'll Be We offer you the flexibility to work where you work best! For this role, you can be within the North Americas region as long as we have a work location. This team operates within the Eastern Standard time zone for collaboration. The United States base range for this position is $227,495- $324,993 plus equity. The benefits available for this position include health insurance, six month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, paid sick leave. These ranges may be modified in the future. Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what's playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It's in our differences that we will find the power to keep revolutionizing the way the world listens. At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we're here to support you in any way we can. Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world's most popular audio streaming subscription service.

About The Team The Deliverability team sits at the core of Uber's delivery marketplace as part of Merchant Optimization. Serving as the critical gating layer for every Uber Eats transaction, our systems answer the fundamental real-time question: "Can this merchant deliver to this eater right now?" We optimize merchant delivery zones to maximize platform selection while balancing marketplace reliability, timeliness, and profitability. The decision made by the deliverability services directly shape selection breadth and business metrics across key downstream platforms, including Search, Feed, and Ads. Role & Responsibilities As a Senior Machine Learning Engineer on the Deliverability team, you will drive the technical vision, end-to-end design, and productionization of core ML systems powering global delivery marketplace decisions. Specifically, you will: Product & Domain ML Architecture: Architect and translate complex marketplace challenges into high-throughput, large scale ML solutions for delivery zone optimization. Design & Train Core Models: Develop, evaluate, and continuously refine state-of-the-art machine learning models that dynamically optimize merchant delivery coverage, balancing conversion, order volume, and fulfillment efficiency. Production Pipelines & ML Infrastructure: Engineer, deploy, and operate scalable ML inference pipelines, feature stores, model serving infrastructure, and automated retraining workflows handling high-throughput global delivery evaluations. Marketplace Optimization & Experimentation: Lead data-driven investigations to diagnose marketplace inefficiencies, execute online A/B testing and leverage telemetry to drive core business metrics. Cross-Functional Technical Leadership: Partner closely with Product Management, Data Science, Operations, and Core Infrastructure teams to align technical roadmaps and define cross-platform ML standards. Basic Qualifications 5+ years of hands-on professional experience designing, training, and operating production ML models at scale. Proactive and strong analytical mindset with a passion for uncovering insights from complex data distributions to drive technical decision-making and project buy-in. Advanced proficiency in Python and mainstream machine learning frameworks (e.g., PyTorch, TensorFlow, Scikit-learn). Solid theoretical foundation in classic and modern ML algorithms, including and not limited to gradient-boosted trees (XGBoost, LightGBM), deep neural networks, and statistical modeling. Proven record of taking complex ML systems end-to-end from initial problem formulation and offline validation to large-scale production deployment. Practical experience developing automated feature engineering pipelines, using feature store technologies, model monitoring platforms, and executing controlled online A/B testing in production. Preferred Qualifications PhD candidate 3+ years of industry experience Experience with geospatial libraries (e.g., H3, S2 Cell). Experience with Graph Neural Networks (GNNs), and/or deep learning recommendation systems. Demonstrated ability to drive cross-functional technical initiatives, mentor junior engineers, and deliver complex multi-phase engineering projects. Familiarity with distributed data processing systems (e.g., Spark, Ray, Flink) and foundational concepts in two-sided marketplace optimization. For San Francisco, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. Ready to Ride? This isn't the kind of place where you follow a playbook - it's where you help write one. If you're driven by impact, energized by challenge, and ready to shape how the world moves - we'd love to hear from you. You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits. Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements. Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.

🚀 Join the Future of Commerce with Whatnot! Whatnot is the largest live shopping platform in North America and Europe to buy, sell, and discover the things you love. Whether it's trading cards, fashion, electronics, or live plants, our sellers are building real businesses across hundreds of categories. We're building live commerce at a scale that's never been done in the West, and there's no playbook to copy. The people here are shaping how an entirely new industry develops. As a remote co-located team, we're inspired by our values and anchored in hubs across the US, UK, Ireland, Poland, Germany, and Australia. We move fast, stay close to our users, and focus on the work that drives the most impact. We're one of the fastest growing marketplaces and were recently named the #1 Best Startup Employer in America by Forbes. Check out the latest Whatnot updates on our news and engineering blogs and join us as we enable anyone to turn their passion into a business and bring people together through commerce. 💻 Role We're looking for entrepreneurial software engineers who thrive on ambiguous, 0-to-1 work. You'll design and deploy both traditional ML models and infrastructure (contextual bandits to manage ad spend, shipment ETA predictions) and LLM-powered systems (RAG pipelines, human-in-the-loop evaluation frameworks) to address the business's most pressing problems. Your job will change every ~12 months as we hand off stable products and pivot to address the business's next big need. Strong applicants display exceptional business judgement and are equally comfortable contributing to production infrastructure and training the models that run on it. They build for the long term while finding ways to aggressively pull forward business impact. What You'll Do Develop and deploy new both production machine learning algorithms and core infrastructure to enrich the buyer and seller experience. Contribute to and set direction across the entire machine learning development process: opportunity sizing, feature engineering, model training, evaluation, load testing, deployment, and alerting. Design and implement supporting software infrastructure to unblock your work: streaming pipelines, async worker queues, event enrichment infrastructure, continuous training loops, model monitoring systems, LLM tool access controls, and dynamic agent evaluation framework to give just a few examples Define project roadmaps that deliver value quickly while building towards scalable, extensible long-term systems Bridge research and production: take an experimental idea and harden it into a scalable, well-tested, monitored system. Communicate tradeoffs and findings clearly to product and leadership. We offer flexibility to work from home or from one of our global office hubs, and we value in-person time for planning, problem-solving, and connection. Team members in this role must live within commuting distance of our Seattle or San Francisco hub. 👋 You Curious about who thrives at Whatnot? We've found that low ego, a growth mindset, and leaning into action and high impact goes a long way here. As our next Software Engineer, Core Machine Learning you should have 4+ years of professional experience, plus: Bachelor's degree in Computer Science, Statistics, Applied Mathematics, or a related technical field, or equivalent work experience. 2+ years of software engineering experience building and maintaining production systems at consumer scale. 2+ years of hands-on experience training and deploying traditional ML models in production (e.g. classification, ranking, or regression models using PyTorch, LightGBM, or scikit-learn) Ability to work autonomously and drive initiatives across multiple product areas and communicate findings with leadership and product teams. Experience with operational, search, and key-value databases such as PostgreSQL, DynamoDB, Elasticsearch, Redis. Firm grasp of visualization tools for monitoring and logging e.g. DataDog, Grafana. Familiarity with cloud computing platforms and managed services such as AWS Kubernetes, Sagemaker, Lambda, Kinesis, S3, EC2, EKS/ECS, Apache Kafka, Flink. Professionalism around collaborating in a remote working environment and well tested, reproducible work. Exceptional documentation and communication skills. 💰Compensation For US-based applicants: $180,000 - $300,000/year + benefits + stock options The salary range may be inclusive of several levels that would be applicable to the position. Final salary will be based on a number of factors including, level, relevant prior experience, skills and expertise. This range is only inclusive of base salary, not benefits (more details below) or equity in the form of stock options. 🎁 Benefits Generous Holiday and Time off Policy Health Insurance options including Medical, Dental, Vision Work From Home Support Home office setup allowance Monthly allowance for cell phone and internet Care benefits Monthly allowance for wellness Annual allowance towards Childcare Lifetime benefit for family planning, such as adoption or fertility expenses Retirement; 401k offering for Traditional and Roth accounts in the US (employer match up to 4% of base salary) and Pension plans internationally Monthly allowance to dogfood the app All Whatnauts are expected to develop a deep understanding of our product. We're passionate about building the best user experience, and all employees are expected to use Whatnot as both a buyer and a seller as part of their job (our dogfooding budget makes this fun and easy!). Parental Leave 16 weeks of paid parental leave + one month gradual return to work *company leave allowances run concurrently with country leave requirements which take precedence. Please note: Whatnot will only contact you through official @whatnot.com email addresses. If you see an email impersonating a Whatnot recruiter, please disregard and report it as spam. 💛 EOE Whatnot is proud to be an Equal Opportunity Employer. We value diversity, and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, parental status, disability status, or any other status protected by local law. We believe that our work is better and our company culture is improved when we encourage, support, and respect the different skills and experiences represented within our workforce. Compensation Range: $180K - $300K

Why USAA? At USAA, our mission is to empower our members to achieve financial security through highly competitive products, exceptional service and trusted advice. We seek to be the #1 choice for the military community and their families. Embrace a fulfilling career at USAA, where our core values – honesty, integrity, loyalty and service – define how we treat each other and our members. Be part of what truly makes us special and impactful. We are proud to support active-duty military spouses. USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with applicable policy and business needs. The Opportunity As a dedicated AI/ML Engineer – Senior Level , you will engage in all phases of the data management and machine learning lifecycles to include requirement analysis, collection, processing, statistical analysis of data, monitoring of model performance, and adhere to related risk requirements. You will develop and maintain technical systems that use machine learning models to make predictions used for classification and/or decision making. What You Will Do Consults with data scientists and business partners on approaches involving ML model development and implementation. Provides technical feedback on ML solutions within technical lead community. Leads the full life cycle of machine learning engineering to include analysis, solution design, data pipeline engineering, testing, deployment, scheduling, application integration, production support, API development, and application integration in support of GenAI applications, ML frameworks/libraires, and ML models. Configure, manage, and set up AI/ML infrastructure components in cloud/on-prem environments for projects and the AI/ML community stakeholders. This includes AWS, GCP, graph databases. Works with architects to influence and define ML model implementation patterns in complex environments. Understand complex model implementation requirements and how to recognize and apply appropriate design patterns throughout solution design and implementation. Designs and implements complex technical solutions for machine learning, artificial intelligence, GenAI, Creates proof of concepts and prototypes on highly complex solutions and presents to leadership to deliver on vision for solution. Assists in setting technical direction for the team and serves as a mentor to team members. Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures. What You Have Bachelor's degree; OR 4 years of relevant education and/or experience. 6 years of machine learning engineering, data engineering, or software development experience implementing data solutions to include 2 years demonstrated technical leadership experience and/or leading teams. Extensive programming experience using Python, Java, or R. Extensive data engineering experience. Experience with end to end delivering of machine learning and AI/GenAI solutions that includes building, integrating, and optimizing data pipelines; curating and modeling the data for various types of consumers/products and their pattern of usage to include data marts, data lake, and operational analytic applications. Experience completing multiple projects leveraging the agile methodology in implementing ML models. Experience leveraging ML Ops principles and implementing automated workflows. Demonstrated ability to mentor junior members of the technical team in area of expertise. Knowledge of Data Science principles and methodologies. Knowledge of stochastic modeling, machine learning, and other advanced mathematical techniques. Effective communication skills, with the ability to present complex technical concepts to both technical and non-technical audiences. Expert knowledge of at least one cloud platform and relevant components e.g., AWS Sagemaker. Compensation range: The salary range for this position is: $143,320 - $273,930 USAA does not provide visa sponsorship for this role. Please do not apply for this role if at any time (now or in the future) you will need immigration support (i.e., H-1B, TN, STEM OPT Training Plans, etc.). Compensation: USAA has an effective process for assessing market data and establishing ranges to ensure we remain competitive. You are paid within the salary range based on your experience and market data of the position. The actual salary for this role may vary by location. Employees may be eligible for pay incentives based on overall corporate and individual performance and at the discretion of the USAA Board of Directors. The above description reflects the details considered necessary to describe the principal functions of the job and should not be construed as a detailed description of all the work requirements that may be performed in the job. Benefits: At USAA our employees enjoy best-in-class benefits to support their physical, financial, and emotional wellness. These benefits include comprehensive medical, dental and vision plans, 401(k), pension, life insurance, parental benefits, adoption assistance, paid time off program with paid holidays plus 16 paid volunteer hours, and various wellness programs. Additionally, our career path planning and continuing education assists employees with their professional goals. For more details on our outstanding benefits, visit our benefits page on USAAjobs.com. Applications for this position are accepted on an ongoing basis, this posting will remain open until the position is filled. Thus, interested candidates are encouraged to apply the same day they view this posting. USAA is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

About The Role We are looking for an experienced Staff Machine Learning Engineer to join Uber's Risk and Trust engineering organization. Our team plays a critical role in protecting users and maintaining the integrity of Uber's global platform through advanced fraud prevention, identity verification, and account security solutions. As fraud threats continue to evolve, including increasingly sophisticated AI-driven attacks, we leverage cutting-edge machine learning techniques to build scalable, intelligent risk detection and prevention systems. In this role, you will lead the development of high-impact ML solutions, tackle complex technical challenges, and collaborate closely with cross-functional partners to deliver measurable business impact while maintaining seamless user experiences. What You'll Do Collaborate with product, data science, and engineering partners to proactively identify high-impact business opportunities, formulate complex ML problems, and help shape the team's technical roadmap. Apply deep expertise in machine learning, optimization, and statistics to design and develop innovative, scalable, and robust ML solutions that drive measurable business impact. Provide technical leadership on complex ML initiatives, drive engineering best practices, and mentor other MLEs to elevate the team's technical capabilities. Own the end-to-end ML development lifecycle, including data preparation, feature engineering, model development, system design, implementation, A/B testing, deployment, and production monitoring. Partner with cross-functional teams to productionize ML solutions at scale. Basic Qualifications 8+ years of industry experience developing machine learning models, including classical ML and deep learning, and deploying ML solutions to production. Master's degree in Computer Science, Engineering, Mathematics, Statistics, or a related technical field. Strong problem-solving skills and a solid foundation in machine learning algorithms, statistics, and optimization. Demonstrated experience applying ML techniques to solve complex, large-scale real-world problems. Proficiency in Python and experience with modern ML frameworks such as PyTorch, TensorFlow, or JAX. Experience building large-scale data pipelines and working with distributed data processing frameworks such as Spark and SQL-based systems. Preferred Qualifications PhD in Computer Science, Engineering, Mathematics, Statistics, or a related technical field. Hands-on experience with advanced ML techniques, such as deep learning, representation learning, sequence modeling, multi-task learning, reinforcement learning or large language models. Experience developing ML solutions for fraud detection, anomaly detection, or other adversarial environments. Demonstrated ability to independently drive complex ML projects from problem formulation through production deployment. Experience working with large-scale, real-time ML systems and making data-driven decisions in production environments. For San Francisco, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. Ready to Ride? This isn't the kind of place where you follow a playbook - it's where you help write one. If you're driven by impact, energized by challenge, and ready to shape how the world moves - we'd love to hear from you. You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits. Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements. Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.

Optum Tech is a global leader in health care innovation. Our teams develop cutting-edge solutions that help people live healthier lives and help make the health system work better for everyone. From advanced data analytics and AI to cybersecurity, we use innovative approaches to solve some of health care's most complex challenges. Your contributions here have the potential to change lives. Ready to build the next breakthrough? Join us in making healthcare work better for everyone through people-led, responsible AI while Caring. Connecting. Growing together. In support of AI 10.0 Scaling and leveraging AI to apply processing rules directly from source documentation via enterprise assets, we're adding resources to our Claim Edit Hub team. This team will work to derive rules/edits directly from source documents (i.e. Policies) and expose them via Agentic workflow to make them accessible in a real time manner. This will also support our "shift left" strategy to enable claim edits/rules to be executed on Trial Claims to provide transparent cost estimates to Providers and Members. You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week. Primary Responsibilities Design, develop, and deploy scalable AI/ML models and automation solutions to solve complex business problems Build and maintain end-to-end ML pipelines including data ingestion, feature engineering, model training, and deployment Develop automation frameworks for model training, testing, validation, and monitoring (MLOps) Collaborate with data science, engineering, product, and business teams to deliver AI-driven solutions Optimize model performance through continuous evaluation, tuning, and retraining strategies Ensure scalability, reliability, and governance of AI models including compliance and data integrity Integrate AI/ML solutions into production systems using CI/CD and cloud platforms Stay updated with emerging AI/ML technologies and automation best practices to drive innovation You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in. #OptumTechPJ Required Qualifications Bachelor's or Master's Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related technical field 5+ years of software engineering, AI engineering, or machine learning engineering experience 3+ years of hands-on experience developing AI/ML solutions, including Generative AI, LLMs, NLP, and traditional machine learning models 3+ years of experience designing, building, and deploying production-grade LLM applications, RAG pipelines, AI agents, and orchestration workflows 5+ years of solid Python development experience supporting AI and data-intensive applications 3+ years of experience with AWS AI and cloud-native services including Bedrock, SageMaker, Lambda, OpenSearch, ECS/EKS, and S3 2+ years of experience with vector databases, embeddings, semantic search, and enterprise knowledge retrieval systems 2+ years of experience implementing MLOps, LLMOps, model monitoring, evaluation frameworks, and AI operationalization practices Preferred Qualifications 2+ years of hands-on experience with Agentic AI frameworks such as LangGraph, Semantic Kernel, CrewAI, AutoGen, MCP, or AgentCore Experience implementing multi-agent architectures and autonomous workflow orchestration Experience with AI evaluation frameworks, hallucination reduction techniques, model benchmarking, and prompt optimization Demonstrated familiarity with Knowledge Graphs, Ontologies, GraphRAG, and enterprise knowledge systems. Experience building reusable AI platform services supporting multiple use cases Experience implementing Retrieval-Augmented Generation (RAG), prompt engineering, semantic search, and knowledge retrieval systems All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy. Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $120,100 - $214,500 annually based on full-time employment. We comply with all minimum wage laws as applicable. Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants. At UnitedHealth Group, our mission is to help people live healthier lives and help make the health system work better for everyone. Together, we are shaping the future of healthcare by harnessing technology and innovation to make care simpler to navigate, more affordable and more connected for the people we serve. We are committed to creating an inclusive workplace where everyone feels welcomed, valued, heard and respected, empowering people to bring their authentic selves to work and strengthening our collective impact through diverse talents, backgrounds, experiences and perspectives. UnitedHealth Group and its affiliated brands are an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations. UnitedHealth Group and its affiliated brands are a drug-free workplace. Candidates are required to pass a drug test before beginning employment. #OptumTechPJ

About Air Apps At Air Apps, we believe in thinking bigger—and moving faster. We're a family-founded company on a mission to create the world's first AI-powered Personal & Entrepreneurial Resource Planner (PRP), and we need your passion and ambition to help us change how people plan, work, and live. Born in Lisbon, Portugal in 2018—and now with offices in both Lisbon and San Francisco—we've remained self-funded while reaching over 100 million downloads worldwide . Our long-term focus drives us to challenge the status quo every day, pushing the boundaries of AI-driven solutions that truly make a difference. Here, you'll be a creative force, shaping products that empower people across the glob e. Join us on this journey to redefine resource management—and change lives along the w ay. The Role A s an AI/ML Eng ineer, you will play a crucial role in designing, developing, and optimizing machine learning models to power our mobile applications. You will work closely with product managers, engineers, and designers to create intelligent, data-driven features that enhance user experiences. Your expertise in artificial intelligence and deep learning will help us innovate and stay ahead in the mobile app indu stry. Please note that this post serves the purpose of enhancing our talent pool while we prepare to launch the official job. As soon as it gets posted we will get in touch wit h you. Responsib ilities Develop, train, and optimize machine learning models for various mobile app f eatures.Research and implement state-of-the-art AI techniques to improve user engagement and app perf ormance.Collaborate with cross-functional teams to integrate AI-driven solutions into our appli cations.Design and maintain scalable ML pipelines, ensuring efficient model deployment and mon itoring.Analyze large datasets to derive insights and drive data-driven decision -making.Stay updated with the latest AI trends and best practices, incorporating them into our development pr ocesses.Optimize AI models for mobile environments to ensure high performance and low latency. Req uirements Around 3+ years of experience in AI/ML development, preferably in mobile app lications.Proficiency in Python, TensorFlow, PyTorch, or other ML f rameworks.Experience with deep learning, NLP, computer vision, and statistical modeling.Familiarity with cloud-based ML services (AWS, Google Cloud, or Azure).Strong understanding of data structures, algorithms, and software engineering best practices.Experience in deploying and maintaining ML models in p roduction.Ability to work collaboratively in a remote team en vironment.Strong problem-solving skills and a passion for i nnovation. What benefits d o we offer? Apple hardware ecosyst em for work.A nnual Bonus.Medical Insurance (including vision &a mp; dental).Disability insurance - short an d long-term.401k up to 4% c ontribution.Air Conference – an opportunity to meet the team, collaborate, and gr ow together.Transport ation budgetFree meal s at the hubGy m membership Diversity &a mp; Inclusion At Air Apps, we are committed to fostering a diverse, inclusive, and equitable workplace. We enthusiastically welcome applicants from all backgrounds, experiences, and perspectives. We celebrate diversity in all its forms and believe that varied voices and experiences mak e us stronger. Applica tion Disclaimer At Air Apps, we value transparency and integrity in our hiring process. Applicants must submit their own work without any AI-generated assistance. Any use of AI in application materials, assessments, or interviews will result in d isqualification. Compensation Ran ge: $100K - $187K