Top AI & Machine Learning Jobs

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.

Own Data, Cloud & AI coverage using a proprietary dataset to produce forward-looking, data-driven research. Analyze trends across AI/ML operations, databases, data integration, governance and cloud infrastructure; produce client-facing insights, thought leadership, and collaborate with product and engineering to improve research methodology and platform fidelity.

Build and publish AI-driven computer vision systems for real-time sports video analysis, large-scale game analytics, and fan-facing features. Collaborate with CMU researchers, take prototypes to production, and mentor students while deploying league-wide analytics platforms.

Design, implement, and evaluate applied research projects to improve alignment, safety, and evaluation of LLM-based guardrails. Work on experiments (e.g., synthetic data quality metrics, explanations for blocked content), deliver results with mentor guidance, and present findings to the team to shape product capabilities.

The role involves developing robust robot policies using reinforcement learning algorithms, enhancing sample efficiency, and applying them to real-world hardware for robotics applications.

AI Residents will develop machine learning algorithms, engage in research, and collaborate with quantitative teams to drive innovation in finance.

Interns will work on AI/ML research in sleep fitness, building prototypes, validating data, and collaborating with a cross-functional team. Expect hands-on mentorship and opportunities for publication.

Lead research and prototype development for generative AI and emerging technologies. Design architectures, build prototypes and proofs-of-concept, evaluate external partners, and collaborate across teams to translate research into production-ready recommendations and solutions.

Conduct market research and competitive analysis on computing and AI hardware/software; author reports and forecasts; maintain market intelligence; promote research through events and press; support sales, business development, and other analysts with client-specific analysis and presentations.

The AI Research Scientist will design, train, and optimize state-of-the-art machine learning models, conduct research on model efficiency, and collaborate with engineering teams to ensure real-world impact.

The Research Scientist will design methods and experiments for AI control and monitoring, focusing on safety and robustness in advanced AI systems. Key tasks include developing monitoring techniques, researching layered control mechanisms, and collaborating with policymakers and industry experts.

Lead applied research to develop and improve biometric algorithms for image quality, recognition (finger, face, iris, scars/marks/tattoo), fusion, and presentation-attack detection. Implement, benchmark, and validate deep-learning and classical CV methods, write near-production code, train and deploy models, publish and patent results, collaborate cross-functionally, and support occasional pre/post-sales activities.

Lead research and product development of document understanding and multimodal AI. Design and evaluate VLMs, RAG and retrieval systems; build benchmarks and datasets; ship production-ready components (table extraction, structure parsing, semantic indexing, multimodal QA); and work with engineering, product, and customers to deploy models and agentic workflows at scale.

Conduct research to develop generative and sampling models for molecular systems, integrating probabilistic inference, deep learning, and reinforcement learning. Design, train, prototype, and benchmark diffusion, autoregressive, flow-based, and latent-variable architectures. Map between simulation and reality, collaborate with chemists and physicists, and work with engineers to deploy scalable research on distributed compute. Contribute end-to-end from ideation to production in a hybrid San Francisco/New York environment.

Lead and build Inflection's realtime Voice AI stack across speech models, streaming systems, voice-agent runtime, and evaluation. Define roadmap, direct research and engineering, design evaluation metrics beyond WER, deploy enterprise voice agents, debug production behavior, and mentor a team focused on speech research, realtime systems, and audio infrastructure.

Lead applied research on continual learning, fast adaptation, memory, and transfer learning for agentic systems. Own end-to-end pipeline from data generation to evaluation and product integration, run experiments, produce code, and drive research strategy while mentoring and managing a small team.

Lead applied research on spatial reasoning, geometric and physical world modeling. Own data generation, evaluation, and product integration. Implement experiments, build production code, and drive research strategy in 3D, multimodal, simulation, and related domains.

As an AI Research Engineer, you'll conduct research in AI and automated reasoning, creating innovative solutions, testing systems, and contributing to scientific publications while collaborating with engineering teams.

Design and optimize high-performance kernels and custom operators for attention, MoE, GEMM, quantization and collective communication across NVIDIA, AMD and AWS Trainium. Improve LLM inference runtimes, develop distributed training/inference solutions at scale, use compilers and SDKs (Neuron, Torch Dynamo, PyTorch/XLA), contribute to open-source, and publish technical findings.

Support AI, analytics, and data modernization for VA research: perform ETL, statistical programming, reporting, dashboards, LLM-enabled analytics, data integration, quality validation, and executive-level presentations to improve operational decision-making.

Develop, mature, prototype, and transition AI and edge software technologies for tactical/disconnected environments. Work with customers, publish research, and advance software engineering for AI-enabled systems. Requires onsite work and background investigation for security clearance.

Design and execute ML research and end-to-end model development for generative and summary-generation systems. Lead rigorous experiments, translate findings for stakeholders, partner with engineers to deploy models, track state-of-the-art advances, and define roadmaps to improve promotional writing and discovery for members.

Develop and operate a system for argumentation related to AI safety, utilizing ontologies and knowledge graphs while collaborating with various stakeholders.

The Research Engineer will develop AI platforms focusing on alignment challenges, multi-agent systems, and optimization algorithms while collaborating on technical publications and prototypes.

Develop and optimize AI models and training systems for robotics applications, focusing on design, implementation, and performance optimization of ML models.