AI Research Intern – Physical AI

🔥 0 minutes ago

🇺🇸 United States – Remote

💵 $45 / hour

⏰ Full Time

⚪️ Entry-level

🧠 AI Research Scientist

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Thermo Fisher Scientific

WebsiteLinkedInAll Job Openings

10,000+ employees

🏥 Healthcare

💼 Consulting

📦 Logistics

Healthcare • Consulting • Logistics

Thermo Fisher Scientific is a leading global supplier of scientific instrumentation, reagents and consumables, and software services. They support the life sciences, healthcare, and analytical chemistry sectors by providing robust solutions for laboratory research and production processes. Their innovative products and services encompass a range of applications, including diagnostics, lab workflow automation, and drug discovery.

📋 Description

• Build and fine-tune models for detection, tracking, segmentation, pose and activity recognition, and scene understanding • Train and evaluate vision-language models for grounding, dense captioning, temporal QA, and tool use • Design retrieval-augmented and agentic loops for perception-action tasks • Prototype perception-in-the-loop policies using simulation and real data • Integrate systems with planners and task graphs for manipulation, navigation, or safety workflows • Curate datasets, author evaluation protocols and KPIs, and run ablations • Package research into reliable services using Kubernetes, Docker, Ray, and FastAPI • Add profiling, telemetry, and CI for reproducible science • Orchestrate multi-agent pipelines combining perception, reasoning, simulation, and code generation • Tackle video understanding, 3D scene grounding, edge inference, multimodal evaluation, and sim-to-real policy evaluation • Deliver publishable or open-source outcomes, production-ready modules, reproducible code, evaluation reports, and demos

🎯 Requirements

• Masters/Ph.D in CS/EE/Robotics (or related), actively publishing in CV/ML/Robotics (e.g., CVPR/ICCV/ECCV, NeurIPS/ICML/ICLR, CoRL/RSS) • 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 • Experience with video models, 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 (TensorRT, ONNX) • 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