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Location: Hybrid, 1 day/week onsite (Dallas or Mountain View) 8–10-year experience Any visa will work Key Requirements Strong hands-on experience building GenAI and LLM-based applications. Experience with RAG (Retrieval Augmented Generation) architecture and AI assistants. Expertise in Prompt Engineering, LLM fine-tuning, evaluation, and model optimization. Strong Python development skills with production-level application experience. Experience with LangChain, LlamaIndex, and Vector Databases. Knowledge of conversational guardrails, AI safety, response validation, and hallucination prevention. Experience deploying scalable AI solutions in AWS or Google Cloud Platform environments.

JOB DESCRIPTION As a Senior Generative AI Engineer, you will lead the design, development, and deployment of production-grade AI solutions. You aren't just building prototypes; you are architecting scalable RAG systems, fine-tuning models for specific domain expertise, and ensuring that GenAI capabilities integrate seamlessly into enterprise-level applications. Key Responsibilities: LLM Orchestration : Design and deploy sophisticated LLM-based applications using frameworks such as LangChain, LlamaIndex, or Semantic Kernel. Model Optimization : Lead the fine-tuning of open-source and proprietary models to improve performance, latency, and cost-efficiency. Advanced RAG Systems : Architect and optimize Retrieval-Augmented Generation (RAG) pipelines utilizing vector databases like Pinecone, FAISS, Weaviate, or Azure AI Search. Scalable Deployment : Containerize services using Docker and deploy via FastAPI and Azure Functions to ensure high availability and low latency. Productization : Build and scale enterprise-grade chatbots, copilots, and automated content generation tools using OpenAI/Azure OpenAI and Hugging Face. Prompt Engineering : Implement and manage advanced prompt optimization and versioning workflows to enhance model accuracy. Monitoring & Evaluation : Establish robust evaluation frameworks (e.g., RAGAS, TruLens) to track model performance, hallucination rates, and drift in production. Operationalization : Collaborate with cross-functional teams (Product, DevOps, Data) to identify high-impact use cases and move them from POC to production. Best Practices : Set the standard for GenAI engineering, including model selection criteria, performance tracking, and ethical AI safeguards. Key Qualifications & Skills Technical Stack : Deep proficiency in Python and GenAI frameworks (LangChain, LlamaIndex). Vector Infrastructure : Hands-on experience with vector indexing, semantic search, and hybrid search strategies. Cloud Proficiency : Strong experience with Azure (Azure OpenAI, Azure Functions, Azure DevOps) or similar cloud ecosystems. Deployment : Experience with CI/CD for AI, MLOps, and containerization. Problem Solving : A proven track record of solving complex "hallucination" and data grounding issues in production environments. Why Join Straive? You will be part of a global footprint spanning 30+ countries, working with a team that is at the forefront of the AI revolution. At Straive, your work directly translates into measurable ROI for the world's leading brands Recognition & Achievements We have been recognized as a Star Performer in Data & AI Services Specialists - Everest's North America PEAK Matrix 2025, and as a Leader in AIM's PeMa Quadrant of Agentic AI Service Providers - 2025. In Nov 2023, Straive acquired Gramener, an award-winning, design-led data science company, enhancing our data, analytics, and AI capabilities. In June 2025, we acquired SG Analytics, a leading provider of AI-powered insights and contextual analytics services. For more information, please visit our Website: https://www.straive.com/ Equal Opportunity Employer Straive is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All employment decisions are based on business needs, job requirements, and individual qualifications, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, or disability status.

Levels 5-7 Location: The Energy Center, Birmingham, AL or Ivan Allen, Atlanta, GA 4 days in-office / 1 day remote Designs, builds, and evolves AI solutions that deliver measurable business and operational value across Southern Power. The AI Engineer translates use-case intent into production-ready agents, models, and workflows, working within the enterprise architectural, governance, and operational standards to ensure solutions are scalable, safe, and fit for a critical-infrastructure environment. JOB REQUIREMENTS: (Experience, Knowledge, Skills ) Domain Expertise Experience building AI and machine learning applications in enterprise settings. Practical understanding of agentic AI concepts, including planners, tool-calling, memory, and multi-agent collaboration. Familiarity with enterprise data platforms and APIs, including structured, unstructured, and document-based data. Awareness of AI governance, risk, and compliance considerations in regulated environments Individual Skills Strong problem-solving skills with the ability to decompose complex use cases into modular agent behaviors. Product-oriented mindset, focused on delivering tangible outcomes rather than experimentation alone. Ability to work effectively within defined architectural and governance constraints. Clear communicator who can explain AI behavior and limitations to non-technical stakeholders. Technical Skills Proficiency in Python and AI frameworks for LLMs and agents. Proficiency with Databricks preferred. Experience with prompt engineering, evaluation techniques, and structured outputs. Familiarity with vector databases, embeddings, and retrieval-augmented generation (RAG) patterns. Working knowledge of API integration and tool execution within agent workflows. Exposure to CI/CD, model deployment, and observability concepts sufficient to operate within pipelines. MAJOR JOB RESPONSIBILITIES: Develop AI solutions. Build and configure agents that reason, plan, and act using models, tools, and enterprise data, aligned to approved patterns. Implement use-case workflows end-to-end. Translate business and operational requirements into AI workflows spanning data ingestion, inference, tool execution, and human-in-the-loop review. Apply responsible AI and guardrails. Embed safety controls, validation steps, and explainability mechanisms into agent logic and prompts by design. Collaborate across the AI delivery lifecycle. Partner with architects on design decisions and with ML Ops to ensure smooth deployment, monitoring, and iteration. Optimize performance and cost. Tune prompts, models, and agent interactions to improve accuracy, latency, and cost efficiency. Support experimentation to production. Rapidly prototype new AI capabilities while adhering to standards that enable promotion to enterprise-grade deployments. Continuously improve agent behavior. Use feedback, evaluations, and operational signals to refine agent performance and reliability over time This position falls under the company's Insider Threat Program and will have access to, and control over sensitive data, systems or assets. Enhanced personnel screening, which includes a background review, drug screen and psychological assessment, will be required if you are selected for this position About Southern Company Southern Company (NYSE: SO ) is a leading energy provider serving 9 million customers across the Southeast and beyond through its family of companies. Providing clean, safe, reliable and affordable energy with excellent service is our mission. The company has electric operating companies in three states, natural gas distribution companies in four states, a competitive generation company, a leading distributed energy solutions provider with national capabilities, a fiber optics network and telecommunications services. Through an industry-leading commitment to innovation, resilience and sustainability, we are taking action to meet customers' and communities' needs while advancing our goal of net-zero greenhouse gas emissions by 2050. Our uncompromising values ensure we put the needs of those we serve at the center of everything we do and are the key to our sustained success. We are transforming energy into economic, environmental and social progress for tomorrow. Our corporate culture has been recognized by a variety of organizations, earning the company awards and recognitions that reflect Our Values and dedication to service. To learn more, visit www.southerncompany.com . Southern Company invests in the well-being of its employees and their families through a comprehensive total rewards strategy that includes competitive base salary, annual incentive awards for eligible employees and health, welfare and retirement benefits designed to support physical, financial, and emotional/social well-being. This position may also be eligible for additional compensation, such as an incentive program, with the amount of any bonus/awards subject to the terms and conditions of the applicable incentive plan(s). A summary of the benefits offered for this position can be found here https://seo.nlx.org/southernco/pdf/SOCO-Benefits.pdf . Additional and specific details about total compensation and benefits will also be provided during the hiring process. Southern Company is an equal opportunity employer where an applicant's qualifications are considered without regard to race, color, religion, sex, national origin, age, disability, veteran status, genetic information, sexual orientation, gender identity or expression, or any other basis prohibited by law. Job Identification: 22357 Job Category: Information Technology Job Schedule: Full time Company: Southern Company Services

Levels 5-7 Location: The Energy Center, Birmingham, AL or Ivan Allen, Atlanta, GA 4 days in-office / 1 day remote Designs, builds, and evolves AI solutions that deliver measurable business and operational value across Southern Power. The AI Engineer translates use-case intent into production-ready agents, models, and workflows, working within the enterprise architectural, governance, and operational standards to ensure solutions are scalable, safe, and fit for a critical-infrastructure environment. JOB REQUIREMENTS: (Experience, Knowledge, Skills ) Domain Expertise Experience building AI and machine learning applications in enterprise settings. Practical understanding of agentic AI concepts, including planners, tool-calling, memory, and multi-agent collaboration. Familiarity with enterprise data platforms and APIs, including structured, unstructured, and document-based data. Awareness of AI governance, risk, and compliance considerations in regulated environments Individual Skills Strong problem-solving skills with the ability to decompose complex use cases into modular agent behaviors. Product-oriented mindset, focused on delivering tangible outcomes rather than experimentation alone. Ability to work effectively within defined architectural and governance constraints. Clear communicator who can explain AI behavior and limitations to non-technical stakeholders. Technical Skills Proficiency in Python and AI frameworks for LLMs and agents. Proficiency with Databricks preferred. Experience with prompt engineering, evaluation techniques, and structured outputs. Familiarity with vector databases, embeddings, and retrieval-augmented generation (RAG) patterns. Working knowledge of API integration and tool execution within agent workflows. Exposure to CI/CD, model deployment, and observability concepts sufficient to operate within pipelines. MAJOR JOB RESPONSIBILITIES: Develop AI solutions. Build and configure agents that reason, plan, and act using models, tools, and enterprise data, aligned to approved patterns. Implement use-case workflows end-to-end. Translate business and operational requirements into AI workflows spanning data ingestion, inference, tool execution, and human-in-the-loop review. Apply responsible AI and guardrails. Embed safety controls, validation steps, and explainability mechanisms into agent logic and prompts by design. Collaborate across the AI delivery lifecycle. Partner with architects on design decisions and with ML Ops to ensure smooth deployment, monitoring, and iteration. Optimize performance and cost. Tune prompts, models, and agent interactions to improve accuracy, latency, and cost efficiency. Support experimentation to production. Rapidly prototype new AI capabilities while adhering to standards that enable promotion to enterprise-grade deployments. Continuously improve agent behavior. Use feedback, evaluations, and operational signals to refine agent performance and reliability over time This position falls under the company's Insider Threat Program and will have access to, and control over sensitive data, systems or assets. Enhanced personnel screening, which includes a background review, drug screen and psychological assessment, will be required if you are selected for this position About Southern Company Southern Company (NYSE: SO ) is a leading energy provider serving 9 million customers across the Southeast and beyond through its family of companies. Providing clean, safe, reliable and affordable energy with excellent service is our mission. The company has electric operating companies in three states, natural gas distribution companies in four states, a competitive generation company, a leading distributed energy solutions provider with national capabilities, a fiber optics network and telecommunications services. Through an industry-leading commitment to innovation, resilience and sustainability, we are taking action to meet customers' and communities' needs while advancing our goal of net-zero greenhouse gas emissions by 2050. Our uncompromising values ensure we put the needs of those we serve at the center of everything we do and are the key to our sustained success. We are transforming energy into economic, environmental and social progress for tomorrow. Our corporate culture has been recognized by a variety of organizations, earning the company awards and recognitions that reflect Our Values and dedication to service. To learn more, visit www.southerncompany.com . Southern Company invests in the well-being of its employees and their families through a comprehensive total rewards strategy that includes competitive base salary, annual incentive awards for eligible employees and health, welfare and retirement benefits designed to support physical, financial, and emotional/social well-being. This position may also be eligible for additional compensation, such as an incentive program, with the amount of any bonus/awards subject to the terms and conditions of the applicable incentive plan(s). A summary of the benefits offered for this position can be found here https://seo.nlx.org/southernco/pdf/SOCO-Benefits.pdf . Additional and specific details about total compensation and benefits will also be provided during the hiring process. Southern Company is an equal opportunity employer where an applicant's qualifications are considered without regard to race, color, religion, sex, national origin, age, disability, veteran status, genetic information, sexual orientation, gender identity or expression, or any other basis prohibited by law. Job Identification: 22357 Job Category: Information Technology Job Schedule: Full time Company: Southern Company Services

Job Number: R0252233 Artificial Intelligence Engineer The Opportunity: As an AI Engineer, you will bring advanced AI capabilities into production systems by integrating models, inference endpoints, agent‑orchestration frameworks, and intelligent workflows into complex, distributed software environments. You will apply strong software engineering principles to ensure these AI features operate reliably, securely, and efficiently at scale. In this role, you will help evolve traditional LLM-driven solutions into goal‑oriented, multi‑agent architectures leveraging agent‑orchestration frameworks, Retrieval-Augmented Generation (RAG), Knowledge Graphs (KGs), and fine‑tuned Small Language Models (SLMs). You will contribute to evaluation and monitoring strategies, refine integration workflows, collaborate with cross‑functional engineering teams, and develop scalable AI capabilities that translate cutting‑edge concepts into operational, mission‑ready solutions. Join us. The world can't wait. You Have: 3+ years of experience developing and maintaining production-grade software systems in Python Experience designing and implementing AI agent architectures using LangChain, LangGraph, AutoGen, MCP, or A2A Experience building RAG solutions with Knowledge Graphs and fine‑tuning SLMs using ONNX, GGML, or Ollama Experience integrating LLMs, external APIs, and distributed services into production with optimized inference workflows Experience developing AI evaluation frameworks, integration tests, and production validation using ReAct patterns and human‑in‑the‑loop methodologies Knowledge of secure HTTP APIs, OAuth2, JWT, API Keys, containerization, and CI/CD pipelines Ability to travel up to 25% of the time TS/SCI clearance Bachelor's degree in Computer Science, Engineering, or Data Science DoD 8140 Level II Certification such as Security+, CySA+, or CISSP Certification Nice If You Have: Experience supporting DoD clients or other federal mission environments Experience with advanced agentic patterns, including prompt caching, guardrails, agent memory, Model Context Protocol (MCP), and agent deployment strategies Experience developing end‑to‑end chatbot or agent‑to‑agent (A2A) systems Experience with enterprise data and machine learning platforms such as Databricks or Snowflake Experience building or managing large‑scale data processing pipelines Master's degree in a related field Clearance: Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information; TS/SCI clearance is required. Compensation At Booz Allen, we celebrate your contributions, provide you with opportunities and choices, and support your total well-being. Our offerings include health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, work-life programs, and dependent care. Our recognition awards program acknowledges employees for exceptional performance and superior demonstration of our values. Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible to participate in Booz Allen's benefit programs. Individuals that do not meet the threshold are only eligible for select offerings, not inclusive of health benefits. We encourage you to learn more about our total benefits by visiting the Resource page on our Careers site and reviewing Our Employee Benefits page. Salary at Booz Allen is determined by various factors, including but not limited to location, the individual's particular combination of education, knowledge, skills, competencies, and experience, as well as contract-specific affordability and organizational requirements. The projected compensation range for this position is $99,000.00 to $225,000.00 (annualized USD). The estimate displayed represents the typical salary range for this position and is just one component of Booz Allen's total compensation package for employees. This posting will close within 90 days from the Posting Date. Identity Statement As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud. Candidate AI Usage Policy AI is a part of our daily work at Booz Allen, and we are committed to the responsible and ethical use of AI tools. However, we want to ensure a fair candidate process based on your own skills and knowledge. As part of this commitment, the use of artificial intelligence (AI) or other tools to assist with responses during interviews (whether in-person or virtual) is prohibited unless permission is explicitly provided . Work Model Our people-first culture prioritizes the benefits of collaboration. To support engagement and effective communication, employees working virtually are generally expected to have their cameras on during meetings. Remote: If this position is listed as remote, there may still be occasions when you are required to work in person at a Booz Allen or customer facility. Hybrid: If this position is listed as hybrid, you will be expected to work from a Booz Allen or customer facility, in alignment with your leadership's expectations and the needs of the role. Onsite: If this position is listed as onsite, work will primarily be performed full-time at a customer facility, where employees will collaborate directly with colleagues and customers as required by the role. Commitment to Non-Discrimination All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law.

Language Model Scientist We're hiring a Language Model Scientist in Santa Clara, California, to join L&T's AI Center of Excellence. You'll build the generative and agentic AI systems that power knowledge, engineering and operations across the L&T Group, turning foundation-model capabilities into secure, reliable and domain-aware solutions: copilots, AI agents, enterprise knowledge systems and natural-language interfaces to engineering and physical systems. What you'll do Fine-tune and align open-source and commercial LLMs (SFT, LoRA/PEFT, RLHF, DPO) for domain tasks such as engineering specifications, contracts, standards and code. Design agentic systems with tool use, planning, memory and multi-agent orchestration, plus RAG and knowledge-graph systems over enterprise data. Build evaluation, guardrail and red-teaming frameworks covering accuracy, hallucination, bias and safety. Deploy and scale LLMs in production (vLLM, TensorRT-LLM, quantization), with monitoring and inference cost optimization across cloud and on-premise. Partner with businesses in Engineering, Manufacturing, Infrastructure, Energy, Financial Services, IT Services and Defence to deliver high-value GenAI use cases. First 12 months Enterprise LLM and agentic AI reference architecture defined for the CoE. 5–8 GenAI and agentic use cases delivered, at least 3 scaled to production. At least one domain-adapted language model developed. LLM evaluation, guardrail and LLMOps framework established. What we're looking for Master's or PhD in Computer Science, AI, NLP, Computational Linguistics or a related field (PhD preferred). 8–15 years in ML or NLP, including 3+ years of hands-on work with LLMs and Generative AI. A track record of building and deploying LLM applications in production at enterprise scale. Deep knowledge of transformer architectures, pre-training, fine-tuning and alignment. Strong Python with PyTorch, Hugging Face, DeepSpeed/FSDP and LLM frameworks such as LangChain, LlamaIndex or LangGraph. Experience with vector databases, knowledge graphs, Model Context Protocol (MCP) and function calling. Plus: engineering, industrial or regulated-domain experience, and publications at ACL, EMNLP, NAACL, NeurIPS, ICML or ICLR. Role details: Reports to the Head, AI Center of Excellence. Headcount: 3. Scope: L&T Group-wide, United States and India. Interested? Apply or send us a message with your profile. #LTGroup #AI #LLM #GenerativeAI #AgenticAI #Hiring #SantaClara

Machine Learning EngineerAbout Blue Voice At Blue Voice our primary mission is to empower first responders with state-of-the-art SaaS solutions, leveraging machine learning and LLMs. We seek to modernize and revolutionize their workflow, response times, and overall efficiency while improving outcomes in the field. We are a venture-backed startup with a lean team distributed across the country and pods on the East and West coasts. The Role Position: Machine Learning Engineer Reports to: Director of ML Location: Remote (US). SF Bay Area preferred, with opportunities for in-person work. Key Responsibilities: Collaborate closely with the Director of ML and the rest of the founding engineering team to design, implement, and iterate on our core SaaS product. Contribute to the full ML lifecycle for products, from design and implementation to evaluation and training, as well as to backend and occasional full-stack initiatives outside the traditional ML scope. Monitor production quality, surface regressions proactively, and help harden existing systems. Triage customer-reported issues end-to-end, identifying root causes and turning them into fixes and eval cases. Keep up to date with the latest developments in ML, specifically in LLMs and RAG, and be comfortable discussing new tools and approaches. Actively participate in product decisions and project deliverables, collaborating across the company with customer success and sales. Basic Qualifications: Bachelor's degree in Computer Science, Engineering, or a related field. 3-4 years of software engineering experience. We weigh what you've built and shipped alongside years of experience and welcome earlier-career applicants with strong work to show. Proficiency in Python and familiarity with modern software development best practices, including integrating AI into the development life cycle. Strong ML fundamentals, specifically LLMs and related technologies. Experience developing and deploying customer-facing SaaS applications. Solid backend fundamentals: APIs, data pipelines, testing, and debugging across service boundaries. Knowledge of or willingness to learn mobile application deployment and integration of ML components with mobile full stack development on React Native. Eligible for CJIS access: you must be a US person able to pass a fingerprint-based background check. Preferred Qualifications: Experience with cloud platforms (e.g., AWS, Azure, GCP) and deploying scalable ML solutions in the cloud. Experience with CI/CD pipelines and Agile methodologies. Prior exposure to, or a strong interest in, the first responder ecosystem or related fields. You'd be a great fit for this role if you: Are a self-starter with the ability to learn new skills quickly and pivot in a fast-evolving environment where development and deployments happen in a matter of days. Bring an opinion. When you find something, say what should change and why. Have a genuine passion for technology, in particular LLMs, and their potential to positively impact society. Benefits: Competitive salary and equity. Opportunities for professional growth and leadership in a fast-growing startup. Flexible working hours and fully remote work. Health and wellness benefits. For more information or to apply, please send your resume accompanied by a brief introduction and any relevant portfolio or project links to amit@bluevoice.io and CC jordan@bluevoice.io Blue Voice is an equal opportunity employer. We are committed to building a diverse and inclusive team and encourage applications from candidates of all backgrounds and experiences.

About Us Think BIG. Achieve More. At City National Bank of Florida, we invest in our people and the communities we serve. Join a team where ambitious careers and meaningful relationships thrive together. We're entrepreneurs at heart—growing fast, making an impact, and shaping the future of banking in Florida. To learn more about City National Bank of Florida visit About Us! Overview City National Bank of Florida is seeking a hands-on Machine Learning / AI Engineer to develop enterprise-grade AI applications, retrieval-augmented generation (RAG) systems, and agentic AI workflows. The engineer will work on real banking use cases involving financial document analysis, credit writing, enterprise knowledge retrieval, risk and fraud prevention, and employee productivity. The ideal candidate combines strong Python software engineering skills with practical experience building, testing, and deploying LLM-powered applications. This is a development-focused role, not a pure research or experimentation position. What You'll Do Design, develop, test, and maintain production-quality Python applications for generative AI and applied machine learning. Build RAG pipelines using document ingestion, parsing, chunking, embeddings, metadata filtering, hybrid search, reranking, and grounded response generation. Develop AI agents and workflow components using LangChain v1 and LangGraph. Integrate Azure OpenAI models and Azure AI Search into enterprise AI applications. Implement structured outputs using Pydantic, schema validation, deterministic business rules, and robust error handling. Build document validation, financial data extraction, summarization, classification, and analysis components. Implement automated evaluation datasets and tests to measure retrieval quality, answer correctness, grounding, and regression. Develop REST APIs and backend services using FastAPI or an equivalent Python framework. Write unit tests, integration tests, and mock-based tests; participate in code reviews and continuous integration. Implement secure handling of sensitive banking information, prompt-injection defenses, input validation, and appropriate AI guardrails. Deploy containerized applications and contribute to Azure monitoring, logging, troubleshooting, and performance optimization. Collaborate with senior engineers, AI leadership, business stakeholders, and risk and compliance teams. Qualifications Programming and software engineering 4–5 years of professional software development experience, with strong hands-on Python proficiency. Strong knowledge of object-oriented programming, data structures, algorithms, modular design, and clean-code principles. Experience with FastAPI, REST APIs, Pydantic, SQL, Git, pytest, and debugging. Generative AI and machine learning Practical experience building LLM-powered applications using OpenAI, Azure OpenAI, or comparable model APIs. Understanding of transformers, embeddings, tokenization, semantic search, and model inference. Hands-on experience with RAG, including document ingestion, chunking strategies, retrieval, grounding, and evaluation. Experience with LangChain, LangGraph, or comparable orchestration frameworks. Direct LangGraph experience is strongly preferred. Experience with prompt design, structured generation, function/tool calling, and output validation. Ability to measure and improve AI quality rather than relying solely on subjective demonstrations. Cloud and engineering practices Experience with Azure or another major cloud platform; Azure experience is preferred. Familiarity with Docker, CI/CD, application logging, monitoring, and automated testing. Ability to troubleshoot API failures, retrieval defects, latency, token usage, and model-related errors. Preferred Qualifications Experience with Azure AI Search, hybrid search, reranking, or vector databases. Experience building AI agents that call enterprise APIs and tools. Familiarity with Model Context Protocol (MCP). Experience with PostgreSQL, Azure Blob Storage, or document-processing pipelines. Experience in banking, financial services, lending, fraud, or another regulated industry. Familiarity with responsible AI, data privacy, and auditability. Education Bachelor's Degree in computer science, data science, engineering, applied mathematics/statistics, information systems, or a related quantitative field (or equivalent combination of education and experience). Master's Degree preferred. Benefits & Perks We offer a competitive benefits package designed to support your success: Health Coverage: Medical, dental, and vision plans with employer contributions. Retirement Savings: 401(k) with matching. Paid Time Off & Holidays: Generous PTO and paid holidays. Wellness Support: Access to mental health and financial wellness resources. Visit our benefits page to learn more Benefits! Join City National Bank of Florida. The possibilities are endless. Special Information To Candidates Equal Opportunity City National Bank of Florida is an Equal Opportunity Employer. We do not discriminate based on race, color, religion, sex, national origin, age, disability, genetic information, protected veteran status, or any status protected by federal, state, or Florida law. We comply with the ADA and applicable Florida laws. Interview Guidelines To ensure a fair and consistent interview process, applicants are not permitted to use AI-enabled devices during interviews, including AI glasses or similar wearable technology that can record, transmit, or generate real-time information. Applicants who require a reasonable accommodation to participate in the interview process should contact talent.attraction@citynational.com in advance of the interview to submit an accommodation request. City National Bank of Florida will engage in the interactive process and provide reasonable accommodations in accordance with applicable law.

See yourself at Dataminr As a Senior AI Engineer at Dataminr, you'll work alongside Research Scientists and Data Scientists to train, adapt, and deploy state-of-the-art LLMs and agents across Predictive, Generative, and Agentic AI. You'll tackle multimodal data, including text, images, video, audio, and sensor data, on a platform that processes billions of inputs every day, helping organizations act on critical events as they unfold. Expect plenty of room to keep growing in both AI and software engineering. This is a hybrid role with two in-office days each week in our New York City or Arlington, VA office. AI Innovation at Dataminr Working at Dataminr you'll have the opportunity to tackle the most exciting trends in AI on a daily basis to power a revolutionary product that uncovers critical events around the world as they unfold. Regenerative AI: our AI technology, ReGenAI, is a new form of generative AI that automatically regenerates real-time Live Event Briefs as events unfold. Learn more here. Agentic AI: we recently launched our Agentic AI capability, what we're calling our Intel Agents, that autonomously generates critical context for our clients on real-time events, threats, and risks allowing them to see the clearest, most accurate view of what's happening on the ground. Learn more here Multimodal AI: our platform detects events from many different types of data (images, video, sensor data, audio, and text in over 150 languages). Learn more here. The opportunity Work with groups of Research Scientists, Engineers, and Data Scientists in the AI Platform organization and beyond, to deploy, build, adapt, optimize, and deploy LLM models in production at very large scale. Own the technical design and implementation of robust API services, libraries, and container strategies that define and support our end-to-end LLMOps lifecycle. Optimize DL/LLM training and inference performance (speed/cost) on specialized hardware. Drive the full lifecycle of complex AI problems: from initial research and literature review to hands-on data exploration, implementation of novel, in-house methods, and successful productization. What You Bring At Dataminr, we value you for who you are. We encourage you to apply for this role, even if you don't meet every qualification. Our candidates are reviewed on the basis of their skill and potential to succeed. M.S. in Computer science or equivalent experience 5+ years of experience as a Research or Machine Learning Engineer. MLOps/LLMOps Experience: building, optimizing, deploying and operating Deep Learning models using PyTorch, including Transformers and LLMs, not just using APIs. Experience working with Research Scientists, reading technical research papers, and implementing state-of-the-art methods in Natural Language Processing, Computer Vision, Knowledge Representation and Management, Vector Databases and Generative AI. Expertise in Python. Experience with Containers, Kubernetes, AWS, Databricks, and Agentic infra such as LangGraph, LangFuse, and vector stores About Dataminr At Dataminr, we are a mission driven team of talented builders, creators and visionaries who have real-world impact on how organizations are able to respond to events. Dataminr's groundbreaking, AI-powered, intelligence platform provides organizations with the earliest signals of emerging risks, events, and threats before they unfold. Trusted by two-thirds of the Fortune 50 and half of the Fortune 100, Dataminr's platform analyzes billions of public data inputs spanning text, image, video, audio and sensor data across 150+ languages, empowering our clients to stay one step ahead in an increasingly complex world where every second counts. Founded in 2009, we have pioneered the world's first real-time event detection platform, long before the recent Gen AI 'boom.' Dataminr operates all around the world united by our passion to use AI for the greater good, be agents of positive change and put our technology into the hands of clients charged with the responsibility to keep organizations running and keep people safe. As our employees focus on developing our revolutionary technology, we focus on our employees. Dataminr is proud to offer a variety of flexible work arrangements, offices all over the world to foster collaboration, generous PTO and sick leave, and more, as part of our competitive benefits package aimed at keeping all our employees happy and healthy. Explore all our benefits here . We believe our differences give us strength. Our employees are empowered to be their best, authentic selves through various opportunities, such as our robust employee resource group (ERG) network, manager development programming, professional development funds, and more. We serve a global community made up of many cultures and strive to reflect the world and clients we serve, with a workforce built on merit and equity. We actively condemn racism and discrimination in any form. We stand for social good, fostering a culture of allyship, and standing up for those who face systemic barriers to equality. We lead with empathy and strive to be agents of positive change in our company and in our communities. The annual base salary range for this position is $154,800 - $227,500. You will also be eligible to receive a discretionary bonus and Company equity. Actual salary will be based on a number of factors including, but not limited to, geographic location, applicant skills, and prior relevant experience. Dataminr is an equal opportunity and affirmative action employer. Individuals seeking employment at Dataminr are considered without regards to race, sex, color, creed, religion, national origin, age, disability, genetics, marital status, pregnancy, unemployment status, sexual orientation, citizenship status or veteran status. Dataminr will collect and process your personal data in accordance with Dataminr's candidate privacy notice available here . By providing your details and applying via our careers website, you acknowledge that you have read our candidate privacy notice. If you have any queries, please contact recruiting@dataminr.com or privacy@dataminr.com . Notice Regarding Automated Employment Decision Tools in New York City

About The Role The role designs and ships production LLM and GenAI systems: retrieval-augmented generation pipelines, agentic workflows, fine-tuning jobs, and evaluation harnesses that hold up under real enterprise traffic. This is not a prompt-tinkering position. The team builds the core AI platform — model serving infrastructure, evaluation frameworks, and RAG architecture — and this role owns meaningful pieces of it end-to-end, working alongside applied scientists, backend engineers, and product leadership. Key Responsibilities Architect and build RAG pipelines using LangChain, LlamaIndex, or custom retrieval stacks, tuning chunking strategies, hybrid search, and reranking for measurable quality gains Implement and scale vector database integrations (Pinecone, Weaviate, pgvector) serving low-latency semantic search in production Design agentic workflows with tool calling, function execution, and guardrails using frameworks like LangGraph or custom orchestration layers Run fine-tuning workloads (LoRA, QLoRA, DPO) on domain-specific datasets using PyTorch and Hugging Face, managing GPU resources across training runs Build systematic LLM evaluation frameworks: golden datasets, LLM-as-judge pipelines, and regression suites wired into CI so quality regressions are caught before deploy Deploy and serve models via vLLM, Triton, or managed inference endpoints, optimizing for cost, latency, and throughput Own observability for GenAI features: tracing with LangSmith or OpenTelemetry, drift detection, and dashboards that surface failure modes quickly What We Are Looking For 3–6 years of software engineering or ML engineering experience, with at least 2 years shipping LLM-powered systems to production Strong Python engineering skills: async programming, API design, testing, and working comfortably in large codebases Hands-on production experience with RAG architecture, including embedding model selection, vector databases, and retrieval quality tuning Experience fine-tuning or evaluating open-source models (Llama, Mistral, Qwen) and working with provider APIs (OpenAI, Anthropic, Bedrock) Working knowledge of cloud infrastructure (AWS, GCP, or Azure), containerized deployments, and GPU-based serving Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience Bonus: experience with RLHF or preference optimization, contributions to open-source LLM tooling, multimodal model experience, or an MS/PhD in a relevant field

Scribd, Inc. is on a mission to advance human understanding. Our four products — Scribd®, Slideshare®, Everand™, and Fable — help billions of people across the globe move beyond access and into insight, application, and expertise. Culture at Scribd, Inc. We support a culture where our employees can be real and be bold; where we debate and commit as we embrace plot twists; and where every employee is empowered to take action as we prioritize the customer. We believe the best work happens when individual flexibility is balanced with meaningful community connection. Scribd Flex empowers employees to choose the workstyle and location that support their best performance, while committing to intentional in-person moments that strengthen collaboration and culture. Occasional in-person attendance is required for all Scribd, Inc. employees, regardless of location. So what are we looking for in new team members? At Scribd, Inc., we hire for "GRIT." Traditionally defined as the intersection of passion and perseverance toward long-term goals, GRIT reflects the mindset we expect from every employee. For us, it also serves as a practical framework for how we work: setting and achieving Goals, delivering Results within your role, contributing Innovative ideas and solutions, and strengthening the broader Team through collaboration and attitude. This posting reflects an approved, open position within the organization. About The Team Premium is the Scribd Inc. pillar behind two reading products: Everand, the audiobook and ebook subscription app, and Fable, the social app where readers track, discuss and discover books. Helping readers find their next book is central to both, so search and recommendations sit at the heart of the products. You'll join Premium's new Discovery squad. It's a small, dedicated group of recommendations, search, applied research and ML engineers working full time on discovery for Everand and Fable. The squad works closely with Orion, Scribd's ML platform team. Orion runs the feature store, model registry, embedding-based retrieval and model serving behind discovery across Scribd, Slideshare and Everand. Role Overview We're looking for a Senior Machine Learning Engineer to own recommendations for Fable and grow into the technical lead for Premium recommendations. Fable's recommender today is a collaborative-filtering model built in house. It has served readers well, but it has no real-time signals and no learned ranking, and it can't recommend to new or lapsed readers. Your first big project is to move Fable onto Orion, so Fable and Everand share a modern recommendation stack. Key Responsibilities Lead the migration of Fable's recommendations onto Orion, covering data, features, training, serving and experiments, while keeping today's recommendations running. Extend Orion's rankers, feature store and embedding-based retrieval to support Fable, in partnership with the Orion ML platform team. Own the health of Fable's recommendation systems in production: quality, latency, cost and on-call. Bring Fable's social signals (shelves, ratings, reviews, book clubs, reader similarity) into recommendations for both Fable and Everand. Design and analyze A/B tests with product managers and analysts to decide what ships. Act as technical lead for Premium recommendations. Shape the roadmap with product managers, and see work that depends on other teams' systems through to delivery. Raise the bar on engineering practice in the squad through design reviews, code quality and operational readiness. Tech you'll work with You'll work across two stacks: Fable's on Google Cloud and Orion's on AWS. Fable: Python (FastAPI, Django), PostgreSQL, BigQuery, Kubernetes, Google Cloud including Vertex AI Orion and Everand: Python, Go and gRPC, Ruby on Rails, Databricks and Spark, Airflow, AWS SageMaker, Weaviate for embedding-based retrieval, feature store and model registry Infrastructure: AWS (EKS, ECS, Lambda, SQS, ElastiCache), Datadog, Terraform Requirements Must have 5+ years as a professional ML or software engineer, with a track record of shipping production ML systems. Hands-on experience building and running recommender systems in production, such as collaborative filtering or matrix factorization, two-tower or embedding retrieval, and learned ranking. Experience with large-scale data processing (Spark, Databricks, BigQuery or similar). Experience on at least one major cloud (AWS or GCP), including deploying services on containers (Kubernetes, ECS or similar). Experience designing and analyzing online experiments. A record of leading projects that depend on other teams, and of working directly with product managers. Bachelor's or Master's degree in Computer Science, or equivalent professional experience. Nice to have Google Cloud experience, especially Vertex AI and BigQuery. Experience migrating or replacing a production ML system while keeping it running. Social or graph-based recommendations, such as user similarity, follows or groups. Search and semantic retrieval (Elasticsearch, Vertex AI Search, vector databases). Experience on consumer apps for reading, media or social. At Scribd, Inc. your base pay is one part of your total compensation package and is determined within a range. Our pay ranges are based on the local cost of labor benchmarks for each specific role, level, and geographic location. San Francisco is our highest geographic market in the United States. In the state of California, the reasonably expected salary range is between $170,000 [minimum salary in our lowest geographic market within California] to $265,000 [maximum salary in our highest geographic market within California]. In the United States, outside of California, the reasonably expected salary range is between $140,000 [minimum salary in our lowest US geographic market outside of California] to $252,000 [maximum salary in our highest US geographic market outside of California]. In Canada, the reasonably expected salary range is between 179,000 CAD[minimum salary in our lowest geographic market] to 237,500 CAD[maximum salary in our highest geographic market]. We carefully consider a wide range of factors when determining compensation, including but not limited to experience; job-related skill sets; relevant education or training; and other business and organizational needs. The salary range listed is for the level at which this job has been scoped. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for a competitive equity ownership, and a comprehensive and generous benefits package. Working at Scribd, Inc. Are you currently based in a location where Scribd, Inc. can employ you? Employees must have their primary residence in or near one of the following cities. This includes surrounding metro areas or locations within a typical commuting distance: United States Atlanta | Austin | Boston | Dallas | Denver | Chicago | Houston | Jacksonville | Los Angeles | Miami | New York City | Phoenix | Portland | Sacramento | Salt Lake City | San Diego | San Francisco | Seattle | Washington D.C. Canada Ottawa | Toronto | Vancouver Mexico Mexico City Benefits At Scribd, Inc. Scribd Flex (flexible work model) Comprehensive health, dental, and vision coverage Mental health support and disability coverage Generous paid time off, including vacation, sick time, holidays, winter break, volunteer time, and sabbaticals Paid parental leave and family support benefits Retirement matching and employee equity Learning and development programs and professional growth opportunities Wellness and home office stipends Complimentary access to the Scribd, Inc. suite of products Enterprise access to leading AI tools Get to Know Scribd, Inc. About Scribd, Inc. Life at Scribd, Inc. We want our interview process to be accessible to everyone. You can inform us of any reasonable adjustments we can make to better accommodate your needs by emailing accommodations@scribd.com about the need for adjustments at any point in the interview process. If you apply for a job with Scribd, Inc. or otherwise engage with us in connection with employment (including as an employee, contractor, or other personnel), the personal information we process in that context is subject to our Employee and Applicant Privacy Policy, which is available here . Scribd, Inc. is committed to equal employment opportunity regardless of race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law. We encourage people of all backgrounds to apply, and believe that a diversity of perspectives and experiences create a foundation for the best ideas. Come join us in building something meaningful.

Scribd, Inc. is on a mission to advance human understanding. Our four products — Scribd®, Slideshare®, Everand™, and Fable — help billions of people across the globe move beyond access and into insight, application, and expertise. Culture at Scribd, Inc. We support a culture where our employees can be real and be bold; where we debate and commit as we embrace plot twists; and where every employee is empowered to take action as we prioritize the customer. We believe the best work happens when individual flexibility is balanced with meaningful community connection. Scribd Flex empowers employees to choose the workstyle and location that support their best performance, while committing to intentional in-person moments that strengthen collaboration and culture. Occasional in-person attendance is required for all Scribd, Inc. employees, regardless of location. So what are we looking for in new team members? At Scribd, Inc., we hire for "GRIT." Traditionally defined as the intersection of passion and perseverance toward long-term goals, GRIT reflects the mindset we expect from every employee. For us, it also serves as a practical framework for how we work: setting and achieving Goals, delivering Results within your role, contributing Innovative ideas and solutions, and strengthening the broader Team through collaboration and attitude. This posting reflects an approved, open position within the organization. About The Team Premium is the Scribd Inc. pillar behind two reading products: Everand, the audiobook and ebook subscription app, and Fable, the social app where readers track, discuss and discover books. Helping readers find their next book is central to both, so search and recommendations sit at the heart of the products. You'll join Premium's new Discovery squad. It's a small, dedicated group of recommendations, search, applied research and ML engineers working full time on discovery for Everand and Fable. The squad works closely with Orion, Scribd's ML platform team. Orion runs the feature store, model registry, embedding-based retrieval and model serving behind discovery across Scribd, Slideshare and Everand. Role Overview We're looking for a Senior Machine Learning Engineer to own recommendations for Fable and grow into the technical lead for Premium recommendations. Fable's recommender today is a collaborative-filtering model built in house. It has served readers well, but it has no real-time signals and no learned ranking, and it can't recommend to new or lapsed readers. Your first big project is to move Fable onto Orion, so Fable and Everand share a modern recommendation stack. Key Responsibilities Lead the migration of Fable's recommendations onto Orion, covering data, features, training, serving and experiments, while keeping today's recommendations running. Extend Orion's rankers, feature store and embedding-based retrieval to support Fable, in partnership with the Orion ML platform team. Own the health of Fable's recommendation systems in production: quality, latency, cost and on-call. Bring Fable's social signals (shelves, ratings, reviews, book clubs, reader similarity) into recommendations for both Fable and Everand. Design and analyze A/B tests with product managers and analysts to decide what ships. Act as technical lead for Premium recommendations. Shape the roadmap with product managers, and see work that depends on other teams' systems through to delivery. Raise the bar on engineering practice in the squad through design reviews, code quality and operational readiness. Tech you'll work with You'll work across two stacks: Fable's on Google Cloud and Orion's on AWS. Fable: Python (FastAPI, Django), PostgreSQL, BigQuery, Kubernetes, Google Cloud including Vertex AI Orion and Everand: Python, Go and gRPC, Ruby on Rails, Databricks and Spark, Airflow, AWS SageMaker, Weaviate for embedding-based retrieval, feature store and model registry Infrastructure: AWS (EKS, ECS, Lambda, SQS, ElastiCache), Datadog, Terraform Requirements Must have 5+ years as a professional ML or software engineer, with a track record of shipping production ML systems. Hands-on experience building and running recommender systems in production, such as collaborative filtering or matrix factorization, two-tower or embedding retrieval, and learned ranking. Experience with large-scale data processing (Spark, Databricks, BigQuery or similar). Experience on at least one major cloud (AWS or GCP), including deploying services on containers (Kubernetes, ECS or similar). Experience designing and analyzing online experiments. A record of leading projects that depend on other teams, and of working directly with product managers. Bachelor's or Master's degree in Computer Science, or equivalent professional experience. Nice to have Google Cloud experience, especially Vertex AI and BigQuery. Experience migrating or replacing a production ML system while keeping it running. Social or graph-based recommendations, such as user similarity, follows or groups. Search and semantic retrieval (Elasticsearch, Vertex AI Search, vector databases). Experience on consumer apps for reading, media or social. At Scribd, Inc. your base pay is one part of your total compensation package and is determined within a range. Our pay ranges are based on the local cost of labor benchmarks for each specific role, level, and geographic location. San Francisco is our highest geographic market in the United States. In the state of California, the reasonably expected salary range is between $170,000 [minimum salary in our lowest geographic market within California] to $265,000 [maximum salary in our highest geographic market within California]. In the United States, outside of California, the reasonably expected salary range is between $140,000 [minimum salary in our lowest US geographic market outside of California] to $252,000 [maximum salary in our highest US geographic market outside of California]. In Canada, the reasonably expected salary range is between 179,000 CAD[minimum salary in our lowest geographic market] to 237,500 CAD[maximum salary in our highest geographic market]. We carefully consider a wide range of factors when determining compensation, including but not limited to experience; job-related skill sets; relevant education or training; and other business and organizational needs. The salary range listed is for the level at which this job has been scoped. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for a competitive equity ownership, and a comprehensive and generous benefits package. Working at Scribd, Inc. Are you currently based in a location where Scribd, Inc. can employ you? Employees must have their primary residence in or near one of the following cities. This includes surrounding metro areas or locations within a typical commuting distance: United States Atlanta | Austin | Boston | Dallas | Denver | Chicago | Houston | Jacksonville | Los Angeles | Miami | New York City | Phoenix | Portland | Sacramento | Salt Lake City | San Diego | San Francisco | Seattle | Washington D.C. Canada Ottawa | Toronto | Vancouver Mexico Mexico City Benefits At Scribd, Inc. Scribd Flex (flexible work model) Comprehensive health, dental, and vision coverage Mental health support and disability coverage Generous paid time off, including vacation, sick time, holidays, winter break, volunteer time, and sabbaticals Paid parental leave and family support benefits Retirement matching and employee equity Learning and development programs and professional growth opportunities Wellness and home office stipends Complimentary access to the Scribd, Inc. suite of products Enterprise access to leading AI tools Get to Know Scribd, Inc. About Scribd, Inc. Life at Scribd, Inc. We want our interview process to be accessible to everyone. You can inform us of any reasonable adjustments we can make to better accommodate your needs by emailing accommodations@scribd.com about the need for adjustments at any point in the interview process. If you apply for a job with Scribd, Inc. or otherwise engage with us in connection with employment (including as an employee, contractor, or other personnel), the personal information we process in that context is subject to our Employee and Applicant Privacy Policy, which is available here . Scribd, Inc. is committed to equal employment opportunity regardless of race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law. We encourage people of all backgrounds to apply, and believe that a diversity of perspectives and experiences create a foundation for the best ideas. Come join us in building something meaningful.