Lab Automation - Vision AI Engineer Intern
About The Position
We are building a next-generation Vision AI platform that enables autonomous laboratory systems to understand, reason about, and interact with complex scientific environments. Our goal is to develop generalized perception and spatial reasoning systems that minimize object-specific model training while enabling robots to interact with previously unseen laboratory equipment and consumables. Rather than training a new model for every instrument, we are building an AI reasoning layer that combines computer vision, multimodal AI, and intelligent workflow orchestration to create scalable laboratory autonomy. As a Vision AI Engineer Intern, you will help design, benchmark, and deploy modern vision and multimodal AI systems while contributing to the architecture that connects perception, reasoning, and autonomous task execution. You will work closely with experienced AI and automation engineers and receive hands-on mentorship while contributing to production systems used in cutting-edge biotechnology research.
Requirements
- Currently pursuing or recently completed a Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Computer Vision, Robotics, or a related field.
- Strong software engineering skills in one or more modern programming languages (e.g., Python, C++, C#), with experience developing AI applications, cloud-based workflows, and production software systems.
- Experience with deep learning frameworks such as PyTorch or TensorFlow.
- Experience developing computer vision or multimodal AI projects through coursework, research, internships, or personal projects.
- Familiarity with object detection, segmentation, tracking, vision-language models, or scene understanding.
- Experience evaluating, training, or fine-tuning AI models.
- Strong curiosity for embodied AI, spatial reasoning, and real-world AI deployment.
Nice To Haves
- Experience with simulation platforms for synthetic or augmented data generation (Isaac Sim, Blender, MuJoCo, Unity, Habitat, etc.).
- Experience with foundation models, multimodal AI, LLMs, or agentic AI frameworks.
- Experience with agentic AI frameworks (LangGraph, OpenAI Agents SDK, AutoGen, PydanticAI), Model Context Protocol (MCP), or AI systems that integrate language models with external tools and software.
- Familiarity with ROS2, MoveIt, SLAM, Foxglove, or robotics software stacks.
- Experience deploying AI models on GPU edge devices (TensorRT, CUDA, ONNX).
- Experience with laboratory automation or scientific instrumentation.
Responsibilities
- Design and develop an AI-driven state-machine architecture that orchestrates perception, reasoning, planning, and downstream task execution for autonomous laboratory workflows.
- Benchmark computer vision, vision-language, and multimodal AI models for accuracy, robustness, inference latency, and deployment cost.
- Design and evaluate AI architectures that combine computer vision, LLMs, and downstream task execution.
- Develop generalized scene understanding and spatial reasoning pipelines that minimize object-specific model training.
- Evaluate approaches for generalized object detection, object relationships, affordance recognition, and intention inference in laboratory environments.
- Build scalable inference pipelines optimized for edge GPUs and cloud deployment.
- Develop synthetic and augmented datasets using simulation platforms to improve model robustness and generalization.
- Design benchmarking frameworks for evaluating perception models across diverse laboratory scenarios.
- Collaborate with automation and robotics engineers to integrate perception systems into autonomous laboratory workflows.
- Document model performance, deployment strategies, and architectural recommendations.
Benefits
- Close mentorship from experienced AI, computer vision, robotics, and automation engineers.
- Opportunity to build AI systems deployed on real robotic platforms operating in cutting-edge biotechnology laboratories.
- Hands-on experience with state-of-the-art vision models, multimodal AI, robotics, GPU computing, and laboratory automation.
- Access to world-class scientists, advanced robotics platforms, and modern AI infrastructure.
- Opportunity to contribute to the next generation of Physical AI for scientific discovery.
- Compensation: $10,000 - $13,000 per month
- Duration: 6 months
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What This Job Offers
Career Level
Intern
Education Level
Associate degree
