Top AI & Machine Learning Jobs

Lead the AI research agenda for Private Assets R&D, developing explainable models for pricing, comparables, nowcasting, and cash-flow forecasting. Design agentic AI workflows, automate research tasks, and translate research into scalable client-facing products. Collaborate with research, product, technology, and data engineering teams while representing the group in client engagements and published research.

Invent and evaluate novel AI/ML methods for large-scale biological data. Design experiments, benchmarks, and reusable modeling frameworks; collaborate with scientists and engineers; publish and share methods to advance scientific discovery.

Conduct research and engineering across computer vision, vision-language models, 3D perception, and physical AI. Build and fine-tune perception and multimodal models, develop perception-to-action policies, curate datasets, design evaluations, run rigorous experiments, and deploy reproducible services using modern AI infrastructure. The role translates published research into prototypes and production-ready modules for robotics, simulation, video understanding, and embodied intelligence.

Lead frontier research in vision AI, multimodal foundation models, simulation-first learning, agentic AI, robotics, and embodied intelligence. Design architectures, training methods, benchmarks, and evaluation frameworks; guide large-scale distributed model development and sim2real integration. Lead researchers, engineers, and interns while mentoring talent, publishing research, developing technical IP, and advancing deployable systems for robotics, autonomous driving, and physical AI.

Lead applied AI research from literature review and foundational research through proof-of-concept development and production deployment. Design and evaluate machine learning, deep learning, reinforcement learning, NLP, computer vision, and prediction models for business-critical challenges. Provide technical leadership, mentorship, strategic direction, and cross-functional collaboration while driving innovation and translating research into measurable business impact.

Design and lead fairness and bias evaluations for AI-assisted People systems across hiring, performance, promotion, development, and workforce planning. Conduct algorithmic audits, subgroup and intersectional analyses, validation studies, counterfactual and generative AI testing, and human-AI workflow evaluations. Build scalable testing, monitoring, documentation, and reporting infrastructure. Partner with engineering, People, legal, privacy, and security stakeholders to recommend mitigations and communicate evidence, risks, limitations, and uncertainty to senior leaders.

Lead product strategy and delivery for Capital Ones AI coding and developer experience tools. Translate frontier AI into governed, developer-loved products that scale AI-augmented workflows, improve code review, embed enterprise standards, and accelerate software delivery through cross-functional leadership and data-driven decisions.

Develop experimental AI techniques for agentic marketing applications, especially image and video generation. Build proofs of concept, autonomous evaluation and improvement systems, realistic AI-generated video, and brand-aligned creative generation workflows. The role requires strong quantitative and probabilistic thinking, backend architecture skills, creativity with LLM applications, and product intuition.

Assist the AI/ML lead in developing and refining retrieval and language-model systems for an intelligence and security research project. Responsibilities include building and evaluating retrieval systems, training or fine-tuning models, attending project meetings, documenting technical discussions, troubleshooting with an interdisciplinary team, and maintaining modular, documented code. The role requires Python, Linux, Git, machine-learning toolkit familiarity, collaboration, and eligibility to obtain a Secret security clearance.

Build and maintain mathematical optimization models for network planning, capacity allocation, routing, and freight operations. Develop production AI applications for process automation, document extraction, and decision support. Establish evaluation, validation, monitoring, and regression-testing frameworks for optimization and AI systems. Identify new business opportunities, prototype solutions, quantify impact, and scale successful initiatives. Partner with operations, pricing, sales, finance, engineering, and leadership to communicate trade-offs and deliver reliable analytical systems.

Conducts fundamental and applied AI and machine learning research, with emphasis on computer vision, agentic AI, deep learning, and predictive modeling. Develops prototypes into operational applications, partners with engineering teams to mature algorithms and deployment pipelines, and establishes evaluation methods. Applies advanced representations, synthetic data, multimodal models, and pose estimation to Army-related missions. Communicates findings through patents, publications, conferences, and code contributions.

Develop and optimize advanced AI models, training pipelines, evaluation frameworks, and debugging systems for robotics applications. Lead rapid experimentation, model architecture development, fine-tuning, performance optimization, and interpretability efforts. Collaborate with engineering teams on training infrastructure and deployment. The role emphasizes ML planning for autonomous vehicles, diffusion and autoregressive models, reinforcement learning, and translating research into production systems.

Develop and apply advanced AI and machine learning methods to aging biology research. Build computational approaches for large-scale biological and imaging data, including computer vision, segmentation, deep learning, generative AI, diffusion, multimodal, and foundation models. Analyze complex datasets, identify biologically meaningful patterns, collaborate with experimental and computational researchers, and help shape research at the intersection of AI, imaging, and aging.

Conduct applied research in generative video and audio synthesis, voice and roomtone cloning, multimodal understanding, computer vision, and speech modeling. Design, implement, test, and evaluate deep learning algorithms, develop new research directions, and help move prototypes into production features. The role requires end-to-end ownership, strong experimental judgment, and the ability to generate and rapidly evaluate machine learning ideas.

Own research-to-prototype pipeline for voice AI and agent orchestration: track emerging techniques, build and evaluate prototypes on real conversation data, run controlled model comparisons, document results, and hand off validated ideas to platform engineers.

Lead design and implementation of generative design, computer vision, geometric deep learning, and reinforcement learning systems for automated building design. Integrate AI with BIM tools, deploy production MLOps pipelines, implement physics-informed models, collaborate with architects/engineers, and publish research to advance AEC-focused AI.

Lead research and implementation of large-scale, multi-task foundation models for dexterous robotic manipulation; manage the data flywheel from specification through collection, training, and real-world evaluation; fine-tune and specialize models; write maintainable Python deep-learning code; and collaborate with Robotics and Hardware teams to deploy models on real robots while co-leading AI engineering efforts.

Lead development of large-scale, multi-task robotic foundation models and manage the data flywheel: specification, collection, training, and real-world evaluation. Implement model specialization and fine-tuning, write production-quality Python for deep learning, and collaborate with robotics and hardware teams to deploy on real robots.

Conduct foundational and applied ML research on AI well-being and moral status, design and run experiments (including tooling/engineering), collaborate with external researchers, and publish papers and public-facing writeups. Evaluate frontier models and present findings to policymakers and industry stakeholders.

As an AI Research Scientist, you will conduct original research in learning-based robotics, working collaboratively with global teams to deploy solutions on actual hardware.

As an AI Research Engineer, you'll design and maintain data pipelines, train models, and work with researchers on innovative solutions.

Seeking an AI Research Engineer to design AI training protocols, build scalable systems, and collaborate on novel AI infrastructure solutions.

Lead engineering of the full embodied systems stack for real-world robots, owning onboard inference, data collection, teleoperation, and on-robot RL systems. Set architecture and technical direction, deliver reliable real-time deployments, close the loop between data, models and actions, and mentor engineers to scale embodied AI in industrial environments.

Develop and deploy foundation and world models (vision-language(-action), multimodal, action-conditioned) for robotic perception, prediction, planning, and high-precision control. Integrate multimodal data, train models for long-horizon planning and simulation, and optimize production-grade models for deployment on RoboForce robotic platforms.

Design and architect AI-powered solutions for higher-education clients, guiding technical feasibility, data pipelines, model orchestration, APIs, observability, and cloud or hybrid deployments. Advise engineering teams, shape reusable patterns, evaluate GenAI/LLM approaches (embeddings, RAG, agents), and mentor junior staff while aligning solutions with client goals and enterprise constraints.