Top AI Research Jobs in Los Angeles, CA

Conduct foundation-model research for robotic manipulation and high-precision manufacturing. Responsibilities include data curation, simulation, model training, evaluation, rigorous testing on industrial robots, and deployment to production hardware. The intern will work independently on ambiguous AI problems, develop multimodal models, use reinforcement or imitation learning, collaborate cross-functionally, and write maintainable production-quality R&D code.

Supports AI safety, robotics, cybersecurity, Physical AI, and advanced mobility projects. Conducts research on standards, regulations, and emerging technologies; assists with safety assurance and consulting activities; develops reports, presentations, workshops, and client deliverables; and contributes to AI safety, cybersecurity, robotics, and technology capabilities.

Manage and coach a team of mentors to ensure delivery outcomes for ~200 AI fellows at scale. Build delivery systems, run operational cadence, lead live instruction when needed, translate field signals into curriculum changes, and partner with strategic partners to close the feedback loop between mentors, fellows, and the curriculum team.

Leads and mentors a team of AI Research and Operations Analysts while scoping organization-wide AI requests, guiding GenAI experimentation, troubleshooting technical and operational issues, and partnering with product, engineering, and business stakeholders. Ensures prototypes, evaluations, automations, and documentation meet quality and business objectives while helping scale AI adoption across the organization.

Leads machine learning research for physical AI and production-scale metal additive manufacturing. Develops hybrid physics-ML models using high-dimensional sensor data, simulation, digital twins, and closed-loop control. Research includes prediction, autonomy, anomaly detection, machine health monitoring, and process optimization. The role validates models against physical outcomes and integrates them into production software and manufacturing workflows while defining technical direction and standards for machine learning applied to physical systems.

Lead research and development of generative AI and recommendation solutions for Netflix promotional assets and content discovery. Responsibilities include tracking LLM research, developing summarization and LLM-as-judge systems, training and evaluating models, optimizing generated content for audience impact, partnering with engineering teams, defining ML roadmaps, and communicating technical strategies to stakeholders.

Establish Rainmaker’s machine learning strategy and deliver operationally useful models for atmospheric science and cloud-seeding operations. Responsibilities include prioritizing ML opportunities, building forecasting and multimodal models, combining radar, satellite, UAS, and in-situ data, creating datasets and evaluation procedures, assessing uncertainty and failure modes, and collaborating with atmospheric scientists and software engineers to productionize successful research.

Annotate and evaluate videos, images, and metadata across major social platforms to support AI system training. Apply contextual and cultural guidelines, resolve ambiguous or sensitive content decisions, perform quality assurance, identify trends and edge cases, conduct root cause analysis, prepare weekly reports, and recommend improvements to labeling processes and tools. The role requires English and Hindi fluency, strong attention to detail, analytical judgment, and comfort handling sensitive content.

Sell, scope, and package AI consulting engagements across enterprise AI GTM categories. Define assessments, workshops, pilots, and multi-phase programs; develop proposals, justify AI infrastructure, drive adoption of workforce AI and coding assistant services; collaborate with sales, architects, and delivery to ensure clean handoffs and measurable outcomes.

The Research Engineer will develop and deploy multimodal AI models, conduct applied research, and contribute to scalable infrastructure for understanding human likeness across modalities.