AI Engineer

• Own 5–15 active model lab relationships as the day-to-day point of contact
• Partner with researchers and product teams to integrate models, run evaluations, and deliver results
• Drive delivery across onboarding, data and product releases, co-launches, and issue resolution
• Own a key process improvement or automation, such as model onboarding, customer data insights, or delivery tooling
• Translate customer feedback and research direction into product ideas and engineering work
• Build and ship pragmatic solutions across the stack for cutting-edge AI teams
• Help expand strategic accounts through trust, execution, and technical judgment

Applied AI Engineer integrating LLMs and building evaluation solutions for Arena Intelligence

Applied AI Engineer

Applied AI Engineer partnering with AI labs to integrate models and deliver evaluations. Building customer-focused TypeScript solutions for Arena Intelligence’s real-world AI assessment platform.

• Design, build, and maintain AI infrastructure for real-time computer vision, LLM, LVM, and multimodal inference workloads
• Build scalable systems for state-of-the-art models across large volumes of video and sensor data
• Optimize inference for latency, throughput, GPU utilization, reliability, and cost
• Develop evaluation harnesses and benchmarking systems for model quality, system performance, regressions, and production readiness
• Build infrastructure for continuous model evaluation, experimentation, and deployment
• Partner with research scientists to productionize advances in computer vision, LLMs, LVMs, RAG, and multimodal AI
• Improve model-serving architecture through batching, caching, routing, quantization, model parallelism, and hardware utilization
• Develop data engines and feedback loops for training data collection, model behavior evaluation, and continuous AI improvement
• Create observability, monitoring, and debugging tools for production AI systems
• Define best practices for deploying, evaluating, and operating AI systems in enterprise environments
• Collaborate with research scientists, product engineering, infrastructure teams, and stakeholders

Software Engineer building AI infrastructure for Ambient.ai’s physical security platform

Software Engineer, AI Infrastructure – LVM Inference & Evaluation

Software Engineer building inference, evaluation, and serving infrastructure for Ambient.ai’s physical security AI platform. Optimizing computer vision, LLM, and multimodal systems for real-time enterprise use.

Machine Learning Engineer

• Design, build, and scale production ML systems spanning deep learning, behavioral modeling, embeddings, and agentic AI
• Architect end-to-end ML systems for high-volume security data
• Turn experiments into reusable capabilities
• Own the ML lifecycle from feature engineering through training, deployment, monitoring, and retraining
• Build LLM and agentic AI capabilities for security investigation, including retrieval-augmented generation
• Design evaluation frameworks to measure model quality and help analysts trust and validate results
• Collaborate with data and platform engineers to scale pipelines and resolve system bottlenecks
• Mentor engineers and guide technical direction through design reviews and hands-on collaboration

Staff Machine Learning Engineer building AI-powered cybersecurity systems at Adobe

Staff Machine Learning Engineer

Staff Machine Learning Engineer building production ML, LLM, and agentic AI systems for Adobe cybersecurity. Designing threat detection, investigation, and security analytics capabilities at scale.

• Build and ship developer-facing features from idea to production
• Own the reliability of shipped products against a constantly changing web
• Turn complex, ambiguous problems into clean APIs
• Participate directly in roadmap decisions and engineering tradeoffs
• Dogfood the product and use GitHub issues and developer feedback to guide development
• Work on the browser-automation and agent-interaction surface
• Ship and own product features used by thousands of developers

Product Engineer building browser automation infrastructure for an AI data platform

Product Engineer – AI Infrastructure, Devtools

Product Engineer building browser automation and agent-interaction tools for an AI data platform. Shipping developer-facing features and reliable APIs used by thousands of developers.

• Develop and improve ads ranking models, including prediction objectives, feature interactions, user-history modeling, and calibration
• Own machine learning systems end-to-end, including data pipelines, feature engineering, training-data construction, model evaluation, model training, and production integration
• Evaluate and apply advances in deep learning and recommendation modeling within production latency, reliability, and cost constraints
• Collaborate with ML platform and product engineers to build scalable and efficient production machine learning systems
• Partner with product, data science, and engineering teams to define ranking objectives, design A/B experiments, and measure advertiser performance, revenue, and user relevance
• Identify opportunities to apply machine learning across the Ads product
• Improve CTR and CVR prediction, model calibration, user and ad representations, and user-sequence modeling
• Translate ranking-quality improvements into advertiser value, revenue, and better user experiences

Senior Machine Learning Engineer optimizing Quora's advertising ranking models

Senior Machine Learning Engineer, Ads

Senior Machine Learning Engineer improving Quora's ad ranking, prediction, and calibration systems. Owning ML research, deployment, experimentation, and production performance at scale.

• Provide technical guidance and support throughout the software development lifecycle
• Collaborate with Product Managers, Architects, DevOps, and QA to design and develop a scalable microservices platform
• Design, develop, and implement high-quality, reusable, and testable code
• Build reusable frameworks
• Work with DevOps and other teams to ensure the platform is highly available, scalable, and fault tolerant
• Handle operational issues with little or no oversight
• Conduct code reviews and ensure adherence to standards, patterns, and architecture principles
• Develop and maintain technical documentation and user guides for the platform

Senior Software Engineer building Ford’s Java cloud-native eCommerce microservices platform

Senior Software Engineer – AI, Search

Senior Software Engineer building Ford’s Java cloud-native eCommerce microservices platform. Designing scalable, fault-tolerant services and search capabilities for future mobility.

• Partner with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products
• Oversee design, development, testing, deployment, and support of AI software components, including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability
• Make build-versus-buy decisions across open-source and SaaS AI technologies
• Invent and introduce state-of-the-art LLM optimization techniques to improve scalability, cost, latency, and throughput of large-scale production AI systems
• Contribute to the technical vision and long-term roadmap of foundational AI systems
• Attract and retain AI talent and nurture team members' personal and professional development
• Mentor and coach team members and foster a culture of learning and staying current with AI developments

Director leading Capital One’s AI infrastructure, optimization, and engineering teams for responsible banking innovation

Director, AI Engineering

Director leading Capital One’s AI infrastructure and optimization systems. Building responsible, scalable AI capabilities that transform customer and associate banking experiences.

• Own greenfield and 0→1 AI systems from technical discovery and architecture through implementation, production launch, monitoring, and iteration
• Design and build production backend services using Python, FastAPI, PostgreSQL, and AWS
• Build and evolve AI-native applications using large language models, AI agents, orchestration, retrieval, tool/function calling, and real-time AI workflows
• Integrate models and services from OpenAI, Anthropic, and other foundation-model platforms
• Design scalable APIs, data models, asynchronous workflows, and distributed services for high-volume AI applications
• Influence architecture across reliability, scalability, latency, observability, security, testing, failure handling, and maintainability
• Establish reusable engineering patterns and technical standards across teams and workstreams
• Evaluate AI behavior in production and build quality measurement, experimentation, evaluation, guardrails, and continuous improvement mechanisms
• Partner with Product and Design to translate customer problems into scalable technical solutions
• Provide hands-on technical leadership across complex cross-functional initiatives
• Participate in design, implementation, debugging, and code review
• Mentor engineers and guide architectural and engineering trade-offs
• Identify technical risks and drive solutions across systems and teams

Staff engineer building AI-powered tax and accounting software at Thomson Reuters

Staff Software Engineer, AI Product Engineering

Staff engineer building AI-powered tax and accounting software at Thomson Reuters. Designing greenfield backend systems and AI-native products from architecture through production.

• Own the architecture and implementation of distributed, high-scale backend systems and APIs that serve machine learning models in production
• Lead technical design for AI integration across product lines, enabling real-time and batch inference workflows using LLMs, transformers, and classification models
• Drive the fine-tuning and deployment of pre-trained models from Hugging Face or OpenAI for mission-critical business use cases
• Integrate external AI services and evaluate build-versus-buy trade-offs
• Define and evolve platform-wide standards for backend engineering, MLOps, model governance, and observability
• Mentor and support senior and mid-level engineers across teams and functions
• Collaborate with product, ML research, data engineering, and DevOps leaders to align technical initiatives with business goals
• Influence AI strategy and roadmap and evaluate emerging technologies and frameworks
• Lead root-cause analyses and performance tuning to ensure reliable, efficient, and scalable systems
• Foodsmart delivers nutrition-driven healthcare, personalized clinical nutrition care, behavior-change tools, and food benefits through its Foodcare platform

Staff AI Engineer scaling AI-powered healthcare systems for Foodsmart’s nutrition platform

Staff AI Engineer

Staff AI Engineer architecting scalable AI and backend systems for Foodsmart’s nutrition-driven healthcare platform. Leading model deployment, MLOps standards, and engineering strategy.

• Develop agents, copilots, and intelligent workflows for caregivers, clinicians, and operational teams
• Build backend services, APIs, data pipelines, integrations, and reusable AI components for reliable production use
• Create systems that extract, retrieve, and reason over clinical documents, conversations, operational records, and structured and unstructured data
• Build representative datasets, measure performance, analyze failures, and improve models, prompts, retrieval, tools, and workflow logic
• Partner with Product, Design, Clinical, and Operations to understand workflows, identify edge cases, and iterate from production feedback
• Write maintainable, well-tested code
• Build shared capabilities for orchestration, tool use, structured outputs, monitoring, tracing, and evaluation
• Ship AI-powered capabilities that solve real problems and progress from prototype to reliable production functionality
• Use evaluations, monitoring, error analysis, and documented limitations to improve system quality
• Develop reusable components and independently own increasingly complex projects and technical decisions
• Determine when to use AI, deterministic software, or human review for the best outcome

Applied AI Engineer building AI-powered home-care products at Abby Care

Applied AI Engineer building reliable AI products and workflow automation for Abby Care’s family-led home-care platform. Developing production systems for caregivers, clinicians, and operations teams.

• Design and architect AI-powered systems using LLMs, retrieval-augmented generation, agentic workflows, and orchestration patterns
• Develop secure, maintainable, production-ready software platforms and cloud-native services
• Orchestrate models, tools, retrieval systems, and enterprise workflows
• Build rapid prototypes and proof-of-concepts to validate technologies and identify business opportunities
• Establish evaluation, monitoring, testing, benchmarking, observability, and continuous-improvement practices
• Lead technical design discussions and architecture reviews
• Drive engineering best practices across teams
• Mentor engineers and develop reusable AI capabilities and frameworks
• Collaborate with product teams, architects, domain experts, customers, and partners
• Identify opportunities and deliver measurable business impact
• Influence IFS’s AI strategy and long-term technology direction through hands-on delivery, experimentation, customer engagement, industry events, and partner collaboration

Lead AI Engineer building enterprise LLM solutions for IFS’s award-winning software

Lead AI Engineer

Lead AI Engineer building production LLM, RAG, and agentic solutions for IFS’s enterprise software. Guiding AI architecture, innovation, and engineering teams.

• Develop artificial intelligence and machine learning solutions to solve business problems and improve member health outcomes
• Develop LLM and generative AI applications, machine learning models, NLP solutions, optimization and mathematical programming, and recommendation systems
• Build and refine data pipelines for feature engineering and ML model input
• Collaborate with data engineering teams to acquire, clean, and prepare training data
• Support model evaluation, testing, and performance monitoring in pre-production environments
• Work within cloud-based ML platforms such as Databricks to develop and optimize AI models
• Collaborate with CI/CD and ML Operations engineers on model deployment and monitoring
• Participate in peer code reviews and follow AI software development best practices
• Develop and refine prompt engineering techniques for LLM and generative AI applications
• Contribute to the AI/ML model lifecycle, ensuring reproducibility, scalability, and maintainability
• Translate business objectives into AI/ML formulations and measurable success criteria
• Optimize and fine-tune models for performance, explainability, and efficiency
• Integrate AI models with enterprise applications, APIs, and data pipelines
• Lead discovery and solutioning to identify high-impact AI opportunities
• Design and implement scalable AI architectures integrated with enterprise systems
• Lead LLM and generative AI initiatives aligned with business needs
• Mentor junior team members and foster engineering excellence
• Recommend best practices for model governance, versioning, and compliance
• Engage leadership and cross-functional teams to align AI strategies with business goals
• Maintain member privacy and adhere to corporate policies and Code of Conduct
• Maintain regular and reliable attendance; perform other assigned functions

AI Engineer developing machine learning and generative AI solutions for Lifetime Healthcare Companies

AI Engineer developing machine learning, LLM, and generative AI solutions for Lifetime Healthcare Companies. Building scalable data pipelines and integrating models with enterprise systems to improve member health outcomes.

• Own the vision, strategy, and roadmap for the company's AI-First Platform
• Lead the transformation from traditional applications to an AI-native platform using agents, workflows, automation, and configurable experiences
• Establish a long-term vision for personalized experiences, configurable applications, and automated business processes
• Conduct customer discovery to understand workflows, pain points, jobs-to-be-done, and emerging AI use cases
• Translate customer and market insights into reusable platform capabilities
• Identify opportunities where AI, automation, and intelligent workflows create customer value and competitive differentiation
• Ensure platform capabilities solve business problems across design, compliance, procurement, supply chain, and operations workflows
• Prioritize investments based on customer value, strategic differentiation, scalability, and business impact
• Partner with Engineering, AI, Architecture, UX, Sales, Marketing, and Customer Success
• Drive roadmap planning, prioritization, execution, and product launches
• Establish success metrics and monitoring frameworks for adoption, engagement, business outcomes, and customer value realization

Senior Product Manager leading Arrow’s AI-first electronics platform strategy and execution

Senior Product Manager – AI Platform

Senior Product Manager defining Arrow’s AI-first platform for electronics workflows. Driving customer discovery, platform roadmaps, AI capabilities, and cross-functional launches.

• Train and evaluate world models on real fleet data collected from autonomous machines in the field
• Run architecture explorations and ablations, and make a defensible case for what is working
• Build evaluation harnesses and metrics to assess model improvements
• Partner with behavior and controls teams to connect model outputs to planning and control
• Present findings and provide a foundation for the team to build upon
• Work on autonomous systems for heavy construction equipment, improving job-site safety and accelerating critical infrastructure schedules

Behavior ML intern building world models for Bedrock Robotics’ autonomous construction equipment

Internship – Behavior Machine Learning Engineer, World Models

Behavior ML intern training world models on fleet data for Bedrock Robotics’ autonomous construction equipment.
Connecting model predictions to planning and control on real excavators.

• Design and build systems for API discovery, schema understanding, and safe agent-to-API orchestration at enterprise scale
• Own search, ranking, relevance, or query-planning problems central to how agents find and use APIs and data
• Prototype quickly, evaluate multiple algorithmic approaches, and iterate based on customer-pilot learnings
• Build and evaluate agentic systems, including tool-calling frameworks, agent orchestration, and observability/evaluation tooling
• Collaborate with a small, high-context team and influence architecture and direction
• Engage with select enterprise customers piloting Constellation to understand usage patterns
• Communicate technical tradeoffs to technical leadership and help shape the roadmap
• Contribute to Apollo's Constellation control plane for AI agents, enabling safe discovery, understanding, and coordination across enterprise APIs

Staff Software Engineer building Apollo's AI-agent API control plane

Staff Software Engineer – AI Runtime

Staff Software Engineer building Apollo's Constellation control plane for AI agents. Designing search, ranking, and safe orchestration across enterprise APIs.

• Improve existing audience acquisition and find new channel or motion opportunities that produce qualified pipeline
• Route each lead into the right follow-up or nurture workflow based on fit, source, intent, and behavior
• Improve conversion from lead to meeting to qualified meeting to S1 with channel-level visibility
• Own the marketing technology and operational layer end to end, including campaigns, copy, workflows, and reporting
• Activate demand by reaching the right audiences and acting on new segments, signals, and channels
• Orchestrate scalable, AI-enabled systems so leads are captured, enriched, routed, nurtured, and converted
• Continuously optimize audience acquisition and conversion through data-driven experiments
• Automate content and workflows to reduce manual work
• Take on broader ownership of Stuut’s channels and acquisition mix as the core funnel improves

GTM Engineer scaling AI-enabled demand generation for Stuut’s accounts-receivable platform

GTM Engineer scaling AI-enabled audience acquisition, lead workflows, and funnel conversion. Building marketing automation for Stuut’s B2B accounts-receivable platform.

• Partner with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products
• Design, develop, test, deploy, and support AI software components, including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability
• Leverage open-source and SaaS AI technologies such as AWS Ultraclusters, Hugging Face, VectorDBs, NeMo Guardrails, and PyTorch
• Invent and introduce state-of-the-art LLM optimization techniques to improve scalability, cost, latency, and throughput of large-scale production AI systems
• Contribute to the technical vision and long-term roadmap of foundational AI systems at Capital One

Senior AI Engineer building scalable responsible AI systems for Capital One banking

Senior AI Engineer

Senior AI Engineer building responsible AI systems for Capital One banking. Developing LLM infrastructure, optimization techniques, and AI-powered customer and associate experiences.

• Lead technical discovery sessions with client business, IT, architecture, security, data, and operations teams
• Translate business objectives and operational challenges into technical requirements, architecture designs, and implementation plans
• Assess enterprise application landscapes, integration requirements, data environments, security constraints, and operating models
• Serve as a trusted technical advisor to clients and internal stakeholders
• Communicate complex AI, data, platform, and integration concepts to technical and executive audiences
• Identify technical risks, dependencies, assumptions, and mitigation strategies
• Develop technical prototypes and proofs of concept
• Design end-to-end solutions connecting AI Agency capabilities with client systems, data sources, content repositories, workflows, and approval environments
• Build and configure production-quality integrations using APIs, webhooks, event-based patterns, secure file exchanges, connector frameworks, and enterprise integration platforms
• Contribute hands-on code across backend services, integration components, data pipelines, AI workflows, and supporting user experiences
• Design and implement AI-enabled workflows using LLMs, RAG, agent orchestration, structured outputs, evaluation frameworks, and human approval checkpoints
• Implement authentication, authorization, identity federation, secrets management, data mapping, error handling, observability, and audit requirements
• Build and maintain data pipelines supporting reporting, analytics, and AI workflows
• Develop cloud-native solutions, preferably on Google Cloud Platform
• Implement CI/CD pipelines and automated deployment processes
• Build and maintain containerized applications using Docker and Kubernetes
• Support monitoring, logging, alerting, observability, production troubleshooting, performance optimization, and incident resolution
• Maintain standards of testing, code quality, scalability, and operational excellence
• Model inclusive behaviors and perform other duties as assigned

Senior AI engineer building generative AI solutions for EVERSANA INTOUCH’s healthcare marketing agency

Senior AI Developer, Engineering

Senior AI engineer building enterprise generative AI, integrations, and workflows for EVERSANA INTOUCH’s life sciences marketing agency. Leading client discovery, architecture, deployment, and cloud operations.

• Work directly with mission users to capture workflows, document operational decision points, and translate them into effective AI-enabled capabilities
• Design and implement LLM-powered workflows, agent-based automation, or hybrid solutions based on mission needs
• Streamline analytical tasks and improve data accessibility
• Support rapid, informed decision-making in high-tempo environments
• Collaborate with operators, analysts, developers, and mission leadership
• Integrate solutions with existing systems
• Ensure solutions perform reliably in production
• Adhere to security and governance expectations of classified environments

Senior AI/ML Engineer building classified workflow automation for Booz Allen’s national-security missions

Senior Artificial Intelligence/Machine Learning Engineer

Senior AI/ML Engineer translating cyber and intelligence workflows into LLM-powered automation for Booz Allen. Building secure, production-ready capabilities for classified national-security environments.

• Build, integrate, test, deploy, and maintain AI agents and supporting applications using Booz Allen’s Agent Foundry platform in AWS
• Connect agents to enterprise data and tools
• Implement retrieval and workflow orchestration
• Integrate ML capabilities
• Evaluate application performance and reliability
• Collaborate with AI/ML engineers, data and cloud engineers, solutions architects, platform developers, and domain subject matter experts
• Translate mission needs into working software
• Support mission readiness assessments, capability gap analysis, knowledge discovery, workflow automation, and computer vision or geospatial analysis
• Own assigned features and contribute to technical design discussions and code reviews
• Troubleshoot issues and improve solutions
• Help deliver mission-focused agents with security controls, traceable outputs, and human oversight

Agentic AI Developer building secure AWS AI agents for Booz Allen’s defense clients

AI Developer

Agentic AI Developer building and deploying secure AWS AI agents for Booz Allen’s defense clients. Integrating enterprise data, workflows, ML capabilities, and mission-focused applications.

Machine Learning Engineer jobs in United States

See all jobs on JobTailor

Applied AI Engineer

Software Engineer, AI Infrastructure – LVM Inference & Evaluation

Staff Machine Learning Engineer

Product Engineer – AI Infrastructure, Devtools

Senior Machine Learning Engineer, Ads

Senior Software Engineer – AI, Search

Director, AI Engineering

Staff Software Engineer, AI Product Engineering

Staff AI Engineer

Applied AI Engineer

Lead AI Engineer

AI Engineer

Senior Product Manager – AI Platform

Internship – Behavior Machine Learning Engineer, World Models

Staff Software Engineer – AI Runtime

Applied AI Engineer

Senior AI Engineer

Senior AI Developer, Engineering

Senior Artificial Intelligence/Machine Learning Engineer

AI Developer