• Lead independent research projects in AI evaluation methodologies, alignment techniques, and synthetic data generation • Design and implement novel evaluation frameworks for LLMs and agent systems that are grounded in human data • Contribute to the academic AI community through publications and open-source contributions • Stay at the forefront of AI research and pioneer innovative approaches to tackle pressing open challenges in the field • Design and conduct rigorous experiments to study AI models and systems with sound methodological approaches • Develop scalable frameworks for systematic evaluation of model behaviours and capabilities • Create tools and frameworks that transform research insights into practical applications • Build infrastructure to support large-scale research experiments when needed • Apply knowledge of model fine-tuning, optimization techniques, distillation, and other ML engineering practices to support research goals • Work closely with ML engineers, data scientists, and product teams to translate research insights into practical applications • Mentor team members on advanced AI concepts and emerging research directions • Communicate complex technical concepts to diverse stakeholders

Role Description Are you pushing the frontier of computer vision, multimodal large models, and embodied/physical AI—and have the publications to show it? Join us to translate cutting-edge research into production systems that perceive, reason, and act in the real world. We are building state-of-the-art Vision AI across 2D/3D perception, egocentric/360° understanding, and multimodal reasoning. As an AI Research Engineer, you will own high-leverage experiments from paper → prototype → deployable module in our platform. We are seeking passionate Engineers to join our cutting-edge labs, you could be part of: - Computer Vision team: Dive into the world of 3D reconstruction, scene understanding, and visual AI. Explore innovative techniques like those used to transform real-world spaces into immersive 3D models. - Physical AI Robotics team: Work at the intersection of simulation, robotics, and AI. Leverage NVIDIA’s Omniverse for advanced 3D simulation and collaboration. What You’ll Do: - Advance Visual Perception: Build and fine-tune models for detection, tracking, segmentation (2D/3D), pose & activity recognition, and scene understanding (incl. 360° and multi-view). - Multimodal Reasoning with VLMs: Train/evaluate vision-language models (VLMs) for grounding, dense captioning, temporal QA, and tool use. - Physical AI & Embodiment: Prototype perception-in-the-loop policies that close the gap from pixels to actions. - Data & Evaluation at Scale: Curate datasets, author high-signal evaluation protocols/KPIs, and run ablations. - Systems & Deployment: Package research into reliable services on a modern stack (Kubernetes, Docker, Ray, FastAPI). - Agentic Workflows: Orchestrate multi-agent pipelines that combine perception, reasoning, simulation, and code generation. Example Problems You Might Tackle: - Long horizon video understanding from egocentric or 360° video. - 3D scene grounding: linking language queries to objects, affordances, and trajectories. - Fast, privacy-preserving perception for on-device or edge inference. - Robust multi-modal evaluation: temporal consistency, open-set detection, uncertainty. - Vision conditioned-policy evaluation in simulation with sim2real stress tests. Qualifications - Masters/Ph.D in CS/EE/Robotics (or related), actively publishing in CV/ML/Robotics. - Strong PyTorch (or JAX) and Python; comfort with CUDA profiling and mixed precision training. - Demonstrated research in computer vision and at least one of: VLMs, embodied/physical AI, 3D perception. - Proven ability to move from paper → code → ablation → result with rigorous experiment tracking. Requirements - Experience with video models (e.g., TimeSFormer/MViT/VideoMAE), diffusion or 3D GS/NeRF pipelines, or SLAM/scene reconstruction. - Prior work on multimodal grounding or temporal reasoning. - Familiarity with ROS2, DeepStream/TAO, or edge inference optimizations. - Scalable training: Ray, distributed data loaders, sharded checkpoints. - Strong software craft: testing, linting, profiling, containers, and reproducibility. - Public code artifacts (GitHub) and first-author publications or strong open source impact. Benefits - Real impact: Your research ships—powering core features in our MVPs and products. - Mentorship: Work closely with our Principal Architect and senior engineers/researchers. - Velocity + Rigor: We balance top-tier research practices with pragmatic product focus. - Salary: $140K - $150K

Role Description You'll work directly on improving how Frontier AI handles corporate finance and gain rare, early exposure to how AI labs actually develop their models. As part of the project, you will contribute your deal experience to a structured research project, which will be used to help improve AI reasoning across investment banking and capital markets. The work involves: - Generating, refining, and evaluating content that reflects how senior IB professionals think through transactions from origination and pitching through execution and close. Qualifications - 3–7 years of experience in investment banking or capital markets at a bulge bracket or elite boutique (e.g., Goldman Sachs, Morgan Stanley, J.P. Morgan, Bank of America, Citi, Barclays, UBS, Deutsche Bank, Wells Fargo, Evercore, Moelis, Centerview, Lazard, Jefferies) - Associate, VP, or Director level across M&A, industry coverage, ECM/DCM, leverage finance, or syndicate - Deep expertise in at least one of: M&A deal structuring and valuation, equity or debt capital markets execution, sector-specific coverage, or syndicate/book-running - Strong financial modeling skills (incl. LBO, 3-statement, DCF) and comfort with complex transaction analysis, fairness opinions, and client-facing materials (incl. pitch decks, market updates) - Ability to articulate investment banking judgment clearly and precisely in writing Requirements - Commitment: 20+ hours/week, flexible scheduling - Location: Fully remote - Compensation: Competitive hourly rate, commensurate with experience - Start date: Immediate / Rolling - Referral bonus: For any successful referral hired into this role How to apply - Apply using the link in the job post - Our team will review the applications and reach back out - One call to assess your fit and align expectations - Once approved, we kick off the project

• Researching and developing advanced healthcare informatics solutions with a specialization in Agentic AI. • Explore applications of Agentic and Generative AI in healthcare. • Develop, analyze, and collaborate on agentic AI projects. • Work closely with cross-functional teams to drive innovative research and practical implementation in healthcare environments.