Bounteous AI Engineer / AI Search Specialist rather than a traditional AWS or Amazon Connect engineer. We are looking for someone with demonstrated experience building and optimizing production-grade AI search and conversational experiences. GenAI & AI Search Hands-on experience with: Retrieval-Augmented Generation (RAG) architectures LLM integration and orchestration Prompt engineering, guardrails, and response grounding Context management and conversational memory Vector search and knowledge retrieval LLM evaluation frameworks, testing, and performance tuning Developing AI responses grounded in enterprise content and knowledge sources Preferred AI Search Domain Experience AI-powered search and question-answering solutions Conversational and chat-based search experiences Citation and source attribution patterns Relevance tuning and retrieval optimization Search analytics, user feedback loops, and answer-quality improvements Healthcare Experience (Preferred) Familiarity with healthcare payer and member-facing experiences Understanding of benefits, claims, eligibility, provider, and healthcare content Experience working in HIPAA-regulated environments Knowledge of responsible AI practices for healthcare use cases Bonus Points Strong AWS Development Experience, Including Amazon Connect Customer Profiles AWS Bedrock AWS Lambda Amazon CloudWatch Amazon Connect Contact Lens Amazon S3 DynamoDB AWS architecture, security, and operational best practices Ideal Candidate We're looking for an engineer who has recently delivered AI-powered search, retrieval, chatbot, or copilot-style solutions in production environments and can contribute immediately to our AI Search roadmap. AWS experience remains valuable, but expertise in GenAI, retrieval, relevance optimization, and LLM evaluation is the primary need for this role.
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Job Title: AI Engineer Location: Coppell, Texas Work Arrangement: On-Site Job Summary We are seeking an AI Engineer to join our engineering team and support AI-driven transformation initiatives within the pharmaceutical industry. The ideal candidate will design, develop, and test AI-powered solutions using AWS AI services, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and advanced prompt engineering techniques. The AI Engineer will work closely with product, design, and engineering teams to develop effective AI workflows, optimize prompts, and integrate local files, documents, and enterprise data sources into AI-powered applications. This role will also focus on AI performance evaluation, security testing, and governance to ensure reliable, secure, and responsible AI implementation. Key Responsibilities Develop and maintain a structured prompt library for common use cases, including summarization, question answering, information extraction, code generation, and file analysis. Apply advanced prompt engineering techniques, including few-shot prompting, role specification, and structured input formats, to improve AI output quality. Design and implement RAG pipelines that connect enterprise systems such as Warehouse Management Systems (WMS), Electronic Data Interchange (EDI) logs, Standard Operating Procedures (SOPs), contract repositories, and other data sources. Develop, deploy, and optimize LLM-powered applications, including internal knowledge assistants and client-facing chat solutions. Extend AI-powered response repositories and identify opportunities to automate workflows, improve processes, and enhance system performance. Conduct A/B testing of prompt variations, evaluate AI-generated responses, and document performance benchmarks. Work with Claude Desktop and similar AI tools to support document-based workflows involving PDFs, Word documents, spreadsheets, and code files. Create reusable prompt patterns for multi-file inputs, long-context documents, and structured data analysis. Develop and maintain internal tools for prompt evaluation, testing, and performance monitoring. Test AI workflows for vulnerabilities, potential bias, and misuse risks while supporting AI safety, security, and governance requirements. Collaborate with cross-functional teams and provide guidance to end users on effective AI tools and prompt usage. Required Skills Experience with Generative AI, Large Language Models (LLMs), and AI application development. Hands-on experience with AWS AI services and cloud-based AI solutions. Strong understanding of prompt engineering, prompt optimization, and LLM evaluation techniques. Experience designing and developing Retrieval-Augmented Generation (RAG) pipelines. Knowledge of enterprise data integration and document-processing workflows. Familiarity with Claude Desktop or similar AI tools for document analysis and file-based workflows. Experience with AI testing, performance benchmarking, and prompt evaluation. Understanding of AI security, data privacy, responsible AI practices, and governance. Strong analytical, problem-solving, communication, and collaboration skills. Preferred Qualifications Experience working with WMS, EDI systems, SOP repositories, contract data, or enterprise knowledge bases. Familiarity with Python, APIs, vector databases, embeddings, and document-processing frameworks. Experience developing AI assistants, enterprise chatbots, or automated document-analysis solutions. Exposure to pharmaceutical, biotechnology, life sciences, or other regulated industry environments.
About Entegrata Entegrata helps law firms turn data into decision-grade insights. Founded in 2023 and headquartered in Indianapolis, we are a venture-backed SaaS company delivering a turnkey, Azure-based data lakehouse platform purpose-built for law firms. Our platform consolidates siloed legal, operational, and financial data into a single governed source of truth, with AI-powered analytics on top. Our mission is to become the data platform of choice for the top law firms in the world. The Role Law firms are pouring both time and money into AI, and many efforts stall on the same point: the data underpinning the endeavor. Your job is to fix that. As our first Applied AI + NLP Engineer, you build the intelligence that turns Entegrata's governed data platform into an enablement layer for a firm's entire AI strategy. You will ship the conversational analytics that let firm leaders interact with their data in plain English and get governed, accurate answers they can act on. In addition to helping unlock value related to structured data from firm systems, you will help us turn legal documents into discrete data. This distillation of documents will help our customers tap into key content with added precision, enabling new insights for customers. You will also build the retrieval and natural-language-to-query capabilities that help firms get more out of the AI tools they already run, and light up new business and practice of law use cases that were not possible before. Because this all sits on top of our governed semantic layer, accuracy, trust, and respect for firm data boundaries are non-negotiable. This is a senior, hands-on role at the core of our AI enablement roadmap. You will need to be comfortable working where data engineering, AI and product intersect. Key Responsibilities AI for Structured Data & Analytics (Initial Focus) Build systems that translate natural language questions into deterministic analytical workflows and governed queries over structured legal data. Help define and implement semantic models and metadata that enable LLMs and AI agents to reason consistently over operational, business, and legal data. Improve intent recognition, query planning, and ambiguity resolution to deliver accurate, consistent responses—even when user requests are incomplete or underspecified. Develop AI agents capable of accessing, interpreting, and synthesizing structured data and legal content to answer complex business questions. Build orchestration logic that intelligently selects the appropriate data sources, models, tools, and workflows for each request. Implement guardrails that ensure AI responses align with governed business definitions, semantic models, and firm conventions. Build evaluation frameworks, benchmark datasets, and automated tests that continuously improve answer quality, determinism, and reliability. Collaborate with Data Engineering to expose governed metrics, dimensions, relationships, and business logic for AI consumption. Document Intelligence & Knowledge Extraction Design and build AI pipelines that transform complex legal documents into structured, machine-understandable data. Help design and evolve legal data models that capture the key concepts, relationships, and business meaning contained within legal documents. Develop techniques to identify legal concepts, obligations, timelines, financial terms, parties, and other domain-specific information that populate and enrich those data models. Design confidence scoring, validation, and human review workflows that improve extraction quality and support continuous model refinement. AI Platform Evolution Optimize AI workflows for quality, latency, scalability, and cost across the platform. Partner closely with Product, Data Engineering, and legal domain experts to translate customer needs into production AI capabilities. Stay current with advances in applied AI, LLMs, and agentic systems, bringing practical innovations into production where they create measurable customer value. What Success Looks Like: 30-60-90 Days First 30 Days | Learn and Contribute Ramp on the platform, semantic layer, and current AI capabilities and evaluation approach. Help create or improve a natural-language query or retrieval flow. By 60 Days | Build and Improve Own an end-to-end AI capability, including its evaluation harness and quality metrics. Deliver the initial design framework for deconstructed legal documents. Measurably improve answer accuracy or reliability on a defined test set. By 90 Days | Own and Lead Deliver production AI features with strong, measured quality and guardrails. Set a technical direction for a piece of the AI roadmap and drive it forward. Establish yourself as a trusted technical partner who can independently design, buils and improve AI capabilities across the Entegrata platform. Required Qualifications 5+ years of software engineering, with hands-on experience building applied AI, NLP, or ML features in production. Practical experience with LLMs: prompting, retrieval-augmented generation, agents, and tool use. Experience with information extraction, document parsing, classification or named entity recognition. Strong evaluation mindset: building test sets and measuring model and system quality. Solid SQL and understanding of structured data and semantic layers. Proficiency in Python and one of Go, .NET, or Node.js. Focus on accuracy, safety, and reliability in customer-facing AI. Preferred Qualifications Experience with natural-language-to-SQL or query generation over governed data. Familiarity with data lakehouse or BI platforms (Databricks, Snowflake, or Microsoft Fabric). Experience with vector / semantic search, embeddings, reranking and hybrid retrieval. Experience building pipelines and processing approaches for long-form or highly structured documents. Legal, finance, or professional services domain exposure. Technology Stack Python, LLM tooling, RAG, vector search, SQL, Azure, Go/.NET/Node.js. Compensation And Benefits Competitive salary, medical, dental, and vision insurance, 401(k) with employer match, unlimited PTO and company holidays, professional development support, and flexible remote work. Equal Opportunity Entegrata is an equal opportunity employer. We celebrate diversity and are committed to building an inclusive environment for all employees. We do not discriminate on the basis of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status, or any other protected characteristic.
CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it's at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. In this role, you will design, build, and deploy AI-powered systems that accelerate AI adoption across CLEAR's internal workflows and customer-facing product experiences. This role will partner directly with Product, Engineering, Data, Security, Legal, Compliance, Operations, and business teams to identify high-impact AI opportunities, rapidly prototype solutions, and productionize reliable, secure, and measurable AI systems. You will own use cases end-to-end, from discovery and evaluation through launch, monitoring, and iteration. What you'll do: Discover, prioritize, and build AI use cases across internal tools, employee workflows, and customer-facing product features Partner with Product, Engineering, Data, Security, Legal, Compliance, and Operations to translate business needs into AI-driven solutions Rapidly prototype AI agents, LLM applications, RAG workflows, automation tools, and product experiences Productionize validated AI use cases with strong evaluation, monitoring, logging, fallback paths, and operational ownership Build reusable patterns for prompt management, retrieval, tool use, evals, guardrails, and human-in-the-loop workflows Implement responsible AI best practices, including privacy, security, model governance, risk review, and customer impact assessment Measure and communicate AI impact across adoption, quality, cost reduction, productivity, customer experience, and business outcomes How you'll measure success: Number of high-impact internal and customer-facing AI use cases launched Adoption and measurable business impact of AI-powered tools and features Quality, reliability, latency, and safety of deployed AI systems Reduction in manual work, operational cost, or customer support volume Improvement in customer experience, containment, accuracy, or workflow efficiency Percentage of AI use cases with clear owners, evals, monitoring, and governance controls Speed from AI opportunity identification to prototype, pilot, and production launch What you're great at: 0-2 years of experience in software engineering, AI engineering, machine learning engineering, data engineering, or related technical roles Some hands-on experience building with LLMs, AI agents, RAG, model APIs, prompt engineering, or AI application frameworks Strong programming skills in Python and/or another modern backend language Some experience building and deploying production systems with APIs, data platforms, cloud infrastructure, logging, monitoring, and testing Ability to work directly with business teams to understand ambiguous workflows and turn them into usable AI products Good product judgment and ability to identify practical, high-ROI AI use cases Knowledge of responsible AI concepts, including evals, guardrails, data privacy, security, human oversight, and model governance Ability to communicate complex technical concepts to technical, non-technical, and executive stakeholders Comfort operating in fast-paced, ambiguous environments with strong ownership from idea to impact Passion for building AI systems that are practical, secure, measurable, and user-centric How You'll be Rewarded: At CLEAR, we help YOU move forward - because when you're at your best, we're at our best. You'll work with talented team members motivated by our mission of making experiences safer and easier. Our offices are bright and energetic with an open concept and plenty of conference rooms and casual co-working spaces. We also offer catered lunches every day and have fully stocked kitchens. Outside of the office, we invest in your well-being and learning & development with stipends and reimbursement programs. We offer holistic total rewards, including comprehensive healthcare plans, family-building benefits (fertility and adoption/surrogacy support), flexible time off, annual wellness stipend, free OneMedical memberships for you and your dependents, a CLEAR Plus membership, and a 401(k) retirement plan with employer match. The base compensation range for this role is $129,500 – $150,500 , depending on levels of skills and experience. Total compensation includes the combined base salary, annual bonus incentive, and new hire equity package (in Restricted Stock Units) for this position at CLEAR. Additionally, this role will be eligible for refresh equity grants as part of our ongoing compensation program. Actual compensation will vary based on factors including, but not limited to, location, education, skills, experience, and performance. All stock based compensation will be subject to the terms and conditions of applicable agreements. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status or other characteristics protected by law. CLEAR provides reasonable accommodation to qualified individuals with disabilities or protected needs. Please let us know if you require a reasonable accommodation to apply for a job or perform your job. Examples of reasonable accommodation include, but are not limited to, time off, extra breaks, making a change to the application process or work procedures, policy exceptions, providing documents in an alternative format, live captioning or using a sign language interpreter, or using specialized equipment. We are committed to a transparent and secure hiring process. All communications related to this role will come directly from a CLEAR employee through valid CLEAR channels (e.g., a valid @clearme.com email address or verified CLEAR LinkedIn profile). We encourage candidates to remain alert to job scams and to report any suspicious activity.
About the role Help train and evaluate AI agents on expert-level fluid simulation tasks. You'll take CAD geometry, set up and run simulations, build verified reference solutions, and write Python checks for the agent's results. Requirements A degree in Mechanical or Aerospace Engineering, or a related field such as energy or oil & gas. A PhD is preferred but not required. Several years of hands-on industry or research CFD with OpenFOAM, ANSYS Fluent/CFX or STAR-CCM+, including meshing. Solid verification and validation practice: mesh-independence studies, and validation against experiment or benchmarks. Comfortable with Python and GitHub. English at B2 level or above. Nice to have: aerospace, automotive, offshore or turbomachinery background; multiphase or particle-laden flow experience. Project time expectations For this project, tasks are estimated to require around 10?20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. Compensation On this project, contributors can earn up to $39 per hour equivalent , depending on their level and pace of contribution. Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements. Why this freelance opportunity might be a great fit for you? Work fully remote on your own schedule with just a laptop and stable internet connection. Apply your expertise to real-world technology projects while gaining experience building high-quality solutions for a global platform. Participate in performance-based bonus programs that reward high-quality work and consistent delivery.
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About the role Help train and evaluate AI agents on expert-level fluid simulation tasks. You'll take CAD geometry, set up and run simulations, build verified reference solutions, and write Python checks for the agent's results. Requirements A degree in Mechanical or Aerospace Engineering, or a related field such as energy or oil & gas. A PhD is preferred but not required. Several years of hands-on industry or research CFD with OpenFOAM, ANSYS Fluent/CFX or STAR-CCM+, including meshing. Solid verification and validation practice: mesh-independence studies, and validation against experiment or benchmarks. Comfortable with Python and GitHub. English at B2 level or above. Nice to have: aerospace, automotive, offshore or turbomachinery background; multiphase or particle-laden flow experience. Project time expectations For this project, tasks are estimated to require around 10?20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. Compensation On this project, contributors can earn up to $39 per hour equivalent , depending on their level and pace of contribution. Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements. Why this freelance opportunity might be a great fit for you? Work fully remote on your own schedule with just a laptop and stable internet connection. Apply your expertise to real-world technology projects while gaining experience building high-quality solutions for a global platform. Participate in performance-based bonus programs that reward high-quality work and consistent delivery.
About the role Help train and evaluate AI agents on expert-level fluid simulation tasks. You'll take CAD geometry, set up and run simulations, build verified reference solutions, and write Python checks for the agent's results. Requirements A degree in Mechanical or Aerospace Engineering, or a related field such as energy or oil & gas. A PhD is preferred but not required. Several years of hands-on industry or research CFD with OpenFOAM, ANSYS Fluent/CFX or STAR-CCM+, including meshing. Solid verification and validation practice: mesh-independence studies, and validation against experiment or benchmarks. Comfortable with Python and GitHub. English at B2 level or above. Nice to have: aerospace, automotive, offshore or turbomachinery background; multiphase or particle-laden flow experience. Project time expectations For this project, tasks are estimated to require around 10?20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. Compensation On this project, contributors can earn up to $39 per hour equivalent , depending on their level and pace of contribution. Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements. Why this freelance opportunity might be a great fit for you? Work fully remote on your own schedule with just a laptop and stable internet connection. Apply your expertise to real-world technology projects while gaining experience building high-quality solutions for a global platform. Participate in performance-based bonus programs that reward high-quality work and consistent delivery.
Become a part of our caring community The Enterprise AI organization at Humana is a pioneering force, advancing AI innovation enterprise-wide across Humana's Insurance, CenterWell, Growth, and Corporate business segments. By collaborating with world-leading experts, we are at the forefront of delivering cutting-edge AI technologies to improve care quality and experience of millions of consumers. We are actively seeking top talent to develop robust and reusable AI modules and pipelines, ensuring adherence to best practices in accountable AI. Join us in shaping the future of healthcare through AI excellence. We are seeking an AI Engineer who will contribute to Generative AI initiatives at Humana, leveraging state-of-the-art LLMs to build applications. Our goal is to create safe AI solutions that will revolutionize and improve healthcare experience and outcomes for our customers. Join our rapidly expanding team of dedicated data scientists, engineers, policy experts, and business leaders as we work together to build impactful and beneficial AI systems. Key Responsibilities AI Innovation & Responsible Generative AI Design and develop AI solutions using Python, AI/ML and generative models like LLMs. Ensure responsible development aligned with Humana's ethical standards, focusing on transparency, safety, and real-world impact. Agentic AI System Design Build autonomous AI agents using frameworks (i.e. LangChain, LangGraph, AutoGen, CrewAI) to support reasoning and decision-making in healthcare. Enterprise Integration & Business Collaboration Embed AI into Humana's systems and workflows. Partner with business teams to understand challenges, co-create solutions, and communicate AI capabilities clearly—especially around generative AI. Design for scalability, reliability, and compliance. MLOps & DevOps Collaboration Work with engineering and product teams to implement best practices for deploying and maintaining AI models in production. Execution of data science initiatives, including design, development, and implementation. Collaborate with data scientists, date engineers, software engineers, and stakeholders to deliver high impact AI use case solutions. Develop and maintain advanced AI/machine learning models and algorithms. Design and implement robust monitoring capabilities to maintain optimal performance and reliability. Experience in creating reports, projections, models, and presentations to business stakeholders. Experience with AI coding assistants Required Qualifications Use your skills to make an impact Bachelor's Degree and 2 or more years of applicable experience OR Master's Degree and 1 or more year of experience preferably with a focus on developing production-ready AI solutions Experience with Agentic AI System Design Experience collaborating with MLOps and DevOps teams Proficiency in SQL, Python, PySpark, and data analysis/data mining tools Experience with machine learning frameworks like Scikit-Learn, Tensorflow, or Pytorch Experience with high performance, large-scale ML systems Experience with language modeling with transformers Experience with large-scale ETL Additional Information Work Style: This position will have a hybrid work style, with 3 days per week in office and 2 days per week remote/home. Office Location Options: Louisville, KY Boston, MA New York, NY Dallas, TX Tampa, FL Washington, DC (Arlington, VA) Scheduled Weekly Hours 40 Pay Range The compensation range below reflects a good faith estimate of starting base pay for full time (40 hours per week) employment at the time of posting. The pay range may be higher or lower based on geographic location and individual pay will vary based on demonstrated job related skills, knowledge, experience, education, certifications, etc. $97,900 - $133,500 per year This job is eligible for a bonus incentive plan. This incentive opportunity is based upon company and/or individual performance. Description Of Benefits Humana, Inc. and its affiliated subsidiaries (collectively, "Humana") offers competitive benefits that support whole-person well-being. Associate benefits are designed to encourage personal wellness and smart healthcare decisions for you and your family while also knowing your life extends outside of work. Among our benefits, Humana provides medical, dental and vision benefits, 401(k) retirement savings plan, time off (including paid time off, company and personal holidays, paid parental and caregiver leave), short-term and long-term disability, life insurance and many other opportunities. About Us About Humana: Humana Inc. (NYSE: HUM) is a leading U.S. healthcare company. Through our Humana insurance services and our CenterWell healthcare services, we make it easier for the millions of people we serve to achieve their best health – delivering the care and service they need, when they need it. These efforts are leading to a better quality of life for people with Medicare and Medicaid, families, individuals, military service personnel, and communities at large. Learn more about what we offer at Humana.com and at CenterWell.com. Equal Opportunity Employer It is the policy of Humana not to discriminate against any employee or applicant for employment because of race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, genetic information, disability or protected veteran status. It is also the policy of Humana to take affirmative action, in compliance with Section 503 of the Rehabilitation Act and VEVRAA, to employ and to advance in employment individuals with disability or protected veteran status, and to base all employment decisions only on valid job requirements. This policy shall apply to all employment actions, including but not limited to recruitment, hiring, upgrading, promotion, transfer, demotion, layoff, recall, termination, rates of pay or other forms of compensation and selection for training, including apprenticeship, at all levels of employment.
Become a part of our caring community The Enterprise AI organization at Humana is a pioneering force, advancing AI innovation enterprise-wide across Humana's Insurance, CenterWell, Growth, and Corporate business segments. By collaborating with world-leading experts, we are at the forefront of delivering cutting-edge AI technologies to improve care quality and experience of millions of consumers. We are actively seeking top talent to develop robust and reusable AI modules and pipelines, ensuring adherence to best practices in accountable AI. Join us in shaping the future of healthcare through AI excellence. We are seeking an AI Engineer who will contribute to Generative AI initiatives at Humana, leveraging state-of-the-art LLMs to build applications. Our goal is to create safe AI solutions that will revolutionize and improve healthcare experience and outcomes for our customers. Join our rapidly expanding team of dedicated data scientists, engineers, policy experts, and business leaders as we work together to build impactful and beneficial AI systems. Key Responsibilities AI Innovation & Responsible Generative AI Design and develop AI solutions using Python, AI/ML and generative models like LLMs. Ensure responsible development aligned with Humana's ethical standards, focusing on transparency, safety, and real-world impact. Agentic AI System Design Build autonomous AI agents using frameworks (i.e. LangChain, LangGraph, AutoGen, CrewAI) to support reasoning and decision-making in healthcare. Enterprise Integration & Business Collaboration Embed AI into Humana's systems and workflows. Partner with business teams to understand challenges, co-create solutions, and communicate AI capabilities clearly—especially around generative AI. Design for scalability, reliability, and compliance. MLOps & DevOps Collaboration Work with engineering and product teams to implement best practices for deploying and maintaining AI models in production. Execution of data science initiatives, including design, development, and implementation. Collaborate with data scientists, date engineers, software engineers, and stakeholders to deliver high impact AI use case solutions. Develop and maintain advanced AI/machine learning models and algorithms. Design and implement robust monitoring capabilities to maintain optimal performance and reliability. Experience in creating reports, projections, models, and presentations to business stakeholders. Experience with AI coding assistants Required Qualifications Use your skills to make an impact Bachelor's Degree and 2 or more years of applicable experience OR Master's Degree and 1 or more year of experience preferably with a focus on developing production-ready AI solutions Experience with Agentic AI System Design Experience collaborating with MLOps and DevOps teams Proficiency in SQL, Python, PySpark, and data analysis/data mining tools Experience with machine learning frameworks like Scikit-Learn, Tensorflow, or Pytorch Experience with high performance, large-scale ML systems Experience with language modeling with transformers Experience with large-scale ETL Additional Information Work Style: This position will have a hybrid work style, with 3 days per week in office and 2 days per week remote/home. Office Location Options: Louisville, KY Boston, MA New York, NY Dallas, TX Tampa, FL Washington, DC (Arlington, VA) Scheduled Weekly Hours 40 Pay Range The compensation range below reflects a good faith estimate of starting base pay for full time (40 hours per week) employment at the time of posting. The pay range may be higher or lower based on geographic location and individual pay will vary based on demonstrated job related skills, knowledge, experience, education, certifications, etc. $97,900 - $133,500 per year This job is eligible for a bonus incentive plan. This incentive opportunity is based upon company and/or individual performance. Description Of Benefits Humana, Inc. and its affiliated subsidiaries (collectively, "Humana") offers competitive benefits that support whole-person well-being. Associate benefits are designed to encourage personal wellness and smart healthcare decisions for you and your family while also knowing your life extends outside of work. Among our benefits, Humana provides medical, dental and vision benefits, 401(k) retirement savings plan, time off (including paid time off, company and personal holidays, paid parental and caregiver leave), short-term and long-term disability, life insurance and many other opportunities. About Us About Humana: Humana Inc. (NYSE: HUM) is a leading U.S. healthcare company. Through our Humana insurance services and our CenterWell healthcare services, we make it easier for the millions of people we serve to achieve their best health – delivering the care and service they need, when they need it. These efforts are leading to a better quality of life for people with Medicare and Medicaid, families, individuals, military service personnel, and communities at large. Learn more about what we offer at Humana.com and at CenterWell.com. Equal Opportunity Employer It is the policy of Humana not to discriminate against any employee or applicant for employment because of race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, genetic information, disability or protected veteran status. It is also the policy of Humana to take affirmative action, in compliance with Section 503 of the Rehabilitation Act and VEVRAA, to employ and to advance in employment individuals with disability or protected veteran status, and to base all employment decisions only on valid job requirements. This policy shall apply to all employment actions, including but not limited to recruitment, hiring, upgrading, promotion, transfer, demotion, layoff, recall, termination, rates of pay or other forms of compensation and selection for training, including apprenticeship, at all levels of employment.
About CFD Research: Since its inception in 1987, CFD Research has delivered innovative technology solutions within the Aerospace & Defense, Biomedical & Life Sciences, Intelligence & Sensing, and Energy & Materials industries. CFD Research has earned multiple national awards for successful application and commercialization of innovative component/system technology prototypes, multi-physics simulation software, multi-disciplinary analyses, and expert support services. Based in Huntsville, Alabama where laboratory facilities and headquarters are located, CFD Research also has office and laboratory facilities in Dayton, Ohio, prototyping test and evaluation facilities in Hollywood, Alabama, and office facilities in Fort Walton Beach, Florida. CFD Research is an ISO9001:AS9100D registered company and is appraised at CMMI Level II for Services. CFD Research is a 100% ESOP (employee-owned company) recognized in Inc. Magazine's Inc5000 as a top growing company for four of the last five years. Learn more at www.cfd-research.com CFD Research is seeking a Senior AI/ML Engineer, to design, build, and deploy advanced artificial intelligence and machine learning solutions that modernize mission systems and accelerate decision‑making across the national security ecosystem. The candidate will contribute end‑to‑end—spanning data processing, model development, MLOps, and integration of scalable AI capabilities into operational environments. The work will leverage deep experience with ML‑based NLP, LLMs and generative AI, computer vision, and modern software engineering practices, consistent with the firm's AI/ML engineering role definitions. We value first-principles reasoning and physically interpretable models, so experience developing hybrid systems that combine calibrated sensor models, deterministic algorithms, probabilistic inference, and learned components is particularly desirable. Candidates should be motivated by building systems that are scientifically explainable, empirically validated, and capable of operating robustly across both synthetic and real-world sensing environments. You will partner closely with cross‑functional engineering, mission SMEs, and product teams to deliver production‑grade systems aligned with Booz Allen's AI modernization approaches. Design, develop, and implement AI/ML models—including NLP, LLM‑based pipelines, deep learning architectures, and computer vision models—aligned to mission requirements Build and optimize scalable data pipelines to support training, evaluation, and continuous improvement of models Develop end‑to‑end production systems including microservices, APIs, automation frameworks, and cloud‑native or edge‑deployed AI services Integrate AI/ML capabilities into operational environments with attention to security, reliability, observability, and performance Conduct model optimization, tuning, versioning, and AB testing to ensure robust mission impact Apply modern software engineering patterns (Python, Java, Scala, Rust; microservices; distributed systems) as consistent with Booz Allen's AI/ML engineering frameworks Collaborate with multi‑disciplinary teams to identify mission needs, gather requirements, and define technical approaches Prepare technical documentation, contribute to design reviews, and support accreditation/security processes as required in classified environments Basic Qualifications Candidate must possess an ACTIVE TS/SCI security clearance to be considered. Experience in GPU programming, including CUDA or RAPIDs Experience with AWS and containerization of models in a classified environment Experience with LLM orchestration, RAG pipelines, grounding, or hallucination‑mitigation workflows Experience with MLOps platforms, distributed training, or hybrid cloud environments (AWS, Azure, GCP) Familiarity with automated testing tools and model evaluation frameworks Master's degree in Computer Science, AI/ML Engineering, Data Science, or related STEM field Industry certifications in AI/ML, cloud, or solution architecture 5+ years of experience developing machine learning models (such as: NLP/LLM, CV, deep learning, generative AI, reinforcement learning, or other related) 5+ years experience developing AI/ML capabilities to operate in a microservice stack Experience developing or maintaining production‑grade APIs, microservices, or distributed systems Experience with data processing frameworks and scientific computing libraries (such as: NumPy, Pandas, PyTorch, TensorFlow, or scikit‑learn) Experience designing, configuring, or deploying software systems in operational environments Experience with CI/CD tooling, source control (such as GitLab) and containerization technologies (such as: Docker, Podman, or Kubernetes) U.S. Citizenship is REQUIRED. Bachelor's degree in a related STEM field Desired Qualifications Experience in GPU programming, including CUDA or RAPIDs Experience with AWS and containerization of models in a classified environment Experience with LLM orchestration, RAG pipelines, grounding, or hallucination‑mitigation workflows Experience with MLOps platforms, distributed training, or hybrid cloud environments (AWS, Azure, GCP) Familiarity with automated testing tools and model evaluation frameworks Master's degree in Computer Science, AI/ML Engineering, Data Science, or related STEM field Industry certifications in AI/ML, cloud, or solution architecture TS/SCI clearance, and willingness to take a polygraph Location: This role is based in the Dayton, OH area , and is 100% onsite. Benefits: CFD Research offers competitive salaries and excellent employee benefits, including an employer matching 401(k) and Employee Stock Ownership Plan (ESOP). CFD Research offers our Full-Time, permanent employee-owners a highly competitive insurance package, including medical, vision, and dental insurance. Additionally, we offer company paid leave, compensation time, parental leave, long-term and short-term disability, accidental death and dismemberment, and life insurance. Part-Time and Temporary employee-owners may receive partial or reduced benefits and leave time based on their employment status level. Performance appraisals occur twice a year and annual pay increases are based upon corporate goals, personal development, performance, and outstanding achievements. In addition, group and individual bonuses are awarded for exceptional performance. CFD Research is an EO employer - Veterans/Disabled and other protected categories
About CFD Research: Since its inception in 1987, CFD Research has delivered innovative technology solutions within the Aerospace & Defense, Biomedical & Life Sciences, Intelligence & Sensing, and Energy & Materials industries. CFD Research has earned multiple national awards for successful application and commercialization of innovative component/system technology prototypes, multi-physics simulation software, multi-disciplinary analyses, and expert support services. Based in Huntsville, Alabama where laboratory facilities and headquarters are located, CFD Research also has office and laboratory facilities in Dayton, Ohio, prototyping test and evaluation facilities in Hollywood, Alabama, and office facilities in Fort Walton Beach, Florida. CFD Research is an ISO9001:AS9100D registered company and is appraised at CMMI Level II for Services. CFD Research is a 100% ESOP (employee-owned company) recognized in Inc. Magazine's Inc5000 as a top growing company for four of the last five years. Learn more at www.cfd-research.com CFD Research is seeking an AI/ML Engineer to build and deploy advanced artificial intelligence and machine learning solutions that l modernize mission systems and accelerate decision-making across the national security ecosystem. The candidate l| will contribute end-to-end—spanning data processing, model development, MLOps, and integration of scalable AI capabilities into operational environments. The work will leverage experience with ML-based NLP, LLMs and generative AI, computer vision, and modern software engineering practices. We value first-principles reasoning and physically interpretable models, so an interest in or experience developing hybrid systems is highly desirable. Candidates should be motivated by building systems that are scientifically explainable, empirically validated, and capable of operating robustly across sensing environments. You will partner with cross-functional engineering, mission SMEs, and product teams to deliver production-grade systems. Develop and implement AI/ML models—including NLP, LLM-based pipelines, deep learning architectures, and computer vision models—aligned to mission requirements. Build and maintain scalable data pipelines to support training, evaluation, and continuous improvement of models. Develop components of end-to-end production systems including microservices, APIs, automation frameworks, and cloud-native AI services. Integrate AI/ML capabilities into operational environments with attention to security, reliability, observability, and performance. Conduct model optimization, tuning, versioning, and A/B testing to ensure robust mission impact. Apply modern software engineering patterns (Python, Java, Scala, Rust; microservices; distributed systems). Collaborate with multi-disciplinary teams to identify mission needs and translate requirements into technical solutions. Prepare technical documentation, contribute to design reviews, and support accreditation processes in classified environments. Basic Qualifications 2–6 years of experience developing machine learning models (such as: NLP/LLM, CV, deep learning, generative AI, or related). 2–6 years of experience developing AI/ML capabilities to operate in a microservice stack. Candidate must possess an ACTIVE TS/SCI security clearance to be considered. Experience working with APIs, microservices, or distributed systems. Experience with data processing frameworks and scientific computing libraries (such as: NumPy, Pandas, PyTorch, TensorFlow, or scikit-learn). Experience configuring or deploying software systems in operational environments. Experience with CI/CD tooling, source control (such as GitLab), and containerization technologies (such as: Docker or Kubernetes). Bachelor's degree in a related STEM field. U.S. Citizenship is REQUIRED. Desired Qualifications Exposure to GPU programming (CUDA or RAPIDs) or AWS containerization. Understanding of LLM orchestration, RAG pipelines, or hallucination mitigation workflows. Familiarity with MLOps platforms or hybrid cloud environments (AWS, Azure, GCP). Familiarity with automated testing tools and model evaluation frameworks. Master's degree in Computer Science, AI/ML Engineering, Data Science, or related STEM field. TS/SCI active, willingness to take a polygraph Location: This role is based in the Dayton, OH area , and is 100% onsite. Benefits: CFD Research offers competitive salaries and excellent employee benefits, including an employer matching 401(k) and Employee Stock Ownership Plan (ESOP). CFD Research offers our Full-Time, permanent employee-owners a highly competitive insurance package, including medical, vision, and dental insurance. Additionally, we offer company paid leave, compensation time, parental leave, long-term and short-term disability, accidental death and dismemberment, and life insurance. Part-Time and Temporary employee-owners may receive partial or reduced benefits and leave time based on their employment status level. Performance appraisals occur twice a year and annual pay increases are based upon corporate goals, personal development, performance, and outstanding achievements. In addition, group and individual bonuses are awarded for exceptional performance. CFD Research is an EO employer - Veterans/Disabled and other protected categories
Snap Inc is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together. The Company operates Snapchat, a visual messaging app that enhances your relationships with friends, family, and the world, and Specs Inc., a wholly-owned subsidiary dedicated to making computing more human, in addition to Bitmoji, Saturn, and other digital services. Snap Engineering teams build fun and technically sophisticated products that reach hundreds of millions of Snapchatters around the world, every day. We're deeply committed to the well-being of everyone in our global community, which is why our values are at the root of everything we do. We move fast, with precision, and always execute with privacy at the forefront. We're looking for a Machine Learning Engineer to join Snap Inc! What you'll do: Build and deploy machine learning models that power core products, serving millions of Snapchatters Apply modern ML techniques to solve large-scale, real-world problems Own the full ML lifecycle from data analysis to production deployment Partner with cross-functional teams to prototype and launch ML-driven features Utilize AI tools to design and ship scalable services while upholding rigorous standards for code correctness, security, and production Knowledge, Skills & Abilities: Strong understanding of machine learning approaches and algorithms Able to prioritize duties and work well on your own Ability to work with both internal and external partners Skilled at solving open ambiguous problems Strong collaboration and mentorship skills Proficiency in, or a strong aptitude for, leveraging AI tools to streamline development, paired with the critical judgment to audit generated output for architectural integrity, performance bottlenecks, and security risks Adaptability in learning and applying evolving AI systems and tools to remain at the forefront of engineering trends and modern development practices Minimum Qualifications: Bachelor's Degree in a relevant technical field such as computer science or equivalent years of practical work experience 5+ years of post-Bachelor's machine learning experience; or Master's degree in a technical field + 4+ year of post-grad machine learning experience; or PhD in a relevant technical field + 1 years of post-grad machine learning experience Experience developing machine learning models for ranking, recommendations, search, content understanding, image generation, or other relevant applications of machine learning Preferred Qualifications: Advanced degree in computer science or related field Experience working with machine learning frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, scikit-learn, or related frameworks Experience working with machine learning, ranking infrastructures, and system design "Default Together" Policy at Snap: At Snap Inc. we believe that being together in person helps us build our culture faster, reinforce our values, and serve our community, customers and partners better through dynamic collaboration. To reflect this, we practice a "default together" approach and expect our team members to work in an office 4+ days per week. At Snap, we believe that having a team of diverse backgrounds and voices working together will enable us to create innovative products that improve the way people live and communicate. Snap is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws. EOE, including disability/vets. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, where applicable). Our Benefits: Snap Inc. is its own community, so we've got your back! We do our best to make sure you and your loved ones have everything you need to be happy and healthy, on your own terms. Our benefits are built around your needs and include paid parental leave, comprehensive medical coverage, emotional and mental health support programs, and compensation packages that let you share in Snap's long-term success! Compensation In the United States, work locations are assigned a pay zone which determines the salary range for the position. The successful candidate's starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. The starting pay may be negotiable within the salary range for the position. These pay zones may be modified in the future. Zone A (CA, WA, NYC): The base salary range for this position is $209,000-$313,000 annually. Zone B: The base salary range for this position is $199,000-$297,000 annually. Zone C: The base salary range for this position is $178,000-$266,000 annually. This position is eligible for equity in the form of RSUs. If you believe this job description is missing required pay transparency information, please submit a report through this form: Job Description Pay Range Disclosure .