Robotics Intern: Systems & Data Platform

Everyone selling a robot has a polished demo and inflated metrics. Almost none have proven performance data from real industrial operations.

Today, buyers are forced to run months-long pilots with every vendor or choose whichever robot looks the best on a presentation.

Deplace is the deployment layer for Physical AI, based on evidence-backed results. We deploy robots on real customer workflows, capture every trial, and continuously evaluate performance using AI-assisted, human-verified measurements, resulting in faster Physical AI development cycles and successful deployments.

We are a VC-funded, well-capitalized startup working at the intersection of Physical AI research and real-world robotics deployment.

This is an open-ended systems and data role with one high-ownership project and a lot of breadth beyond it. You will be developing custom tools and standardized setups that make our tech stack and data flow more efficient.

Beyond that, you will be collaborating with the team on our annotation pipelines, fine-tuning VLA models, processing multimodal data, and the cloud infrastructure underneath it all.

• Designing and deploying camera rigs: mounting, calibration, and drift detection that stay reliable in unpredictable, real-world environments.
• Automating data ingestion, sync, and validation with frame-level fault detection and quality monitoring.
• Extending the annotation pipeline to reduce reliance on manual labeling.
• Writing production-quality code that is traceable, reproducible and modular.
• Brainstorming with us as we grow the company. Helping drive strategy is worth more than closing tickets.

• Strong foundation in Python and perception fundamentals: cameras, calibration, and signal processing.
• Familiarity with robot hardware, and the ability to debug failures through hardware-in-the-loop testing.
• A deployed system, publication, thesis or a personal/open-source project. A flagship you can speak about for hours.
• High agency. Ability to break down problems and make autonomous decisions, and know when to seek guidance.

Ideal candidates have three or more of the following.

• Experience with multi-camera calibration or sensor fusion
• You’ve used OpenCV, GStreamer, FFmpeg, or similar video tooling in a project
• Built data feeding pipelines for VLM/VLA models
• Comfortable with cloud infrastructure: storage, compute, deployment
• Familiarity with multimodal datasets, LeRobot, or comparable tooling
• Owned a large subsystem through FIRST Robotics, BattleBots, Formula Student, or a comparable project
• Experience with agentic workflows and token/inference optimization

• Location: San Francisco Bay Area (hybrid), with the possibility of remote work.
• Duration: ~3 months with flexible timings.
• Start: As soon as possible (rolling applications)
• Compensation: Based on qualifications and experience
• Scope: Personalized for each candidate. High ownership of a project, with a lot of breadth.