VP of Engineering

Build and run the engineering behind a foundation model for embodied behavior. From research to products in the real world, in real time.

Thespian Labs is an embodied intelligence research lab with roots at MIT. We are building a foundation model for behavior, the layer between reasoning and execution where a body has to do something coherent while the world keeps moving. Reasoning can plan and decide. Execution can render pixels and drive motors. The layer in between is the one nobody has built, and it is the whole of our work.

About the Role

As VP of Engineering at Thespian Labs, you will build the team and run the engineering that turns our research into products in the real world. Our models have to perceive, act, and speak inside a body in real time, while the world keeps moving, and getting there is as much an engineering problem as a research one. You will run all of product engineering, the delivery and deployment of what we ship, cloud operations, and the MLOps and real-time inference that put models into production.

This is a hands-on leadership role on a small team, where you write code and set direction in equal measure. You will hire and grow the engineers around you, establish the practices that keep us fast without breaking what matters, and shape the technical roadmap alongside research. The loop is short, so the systems you build ship quickly and run in the real world.

Responsibilities

• Build and lead the engineering team, hiring, mentoring, and growing the engineers, and setting the culture and structure that keep a small team fast.
• Run all of product engineering, everything we ship, from the foundation model platform to the agent products built on top of it.
• Drive product delivery and deployment end to end, the release pipelines and CI/CD that move a working build to customers on a fast, dependable cadence.
• Manage cloud operations and infrastructure, the platform our systems run on, including provisioning, scaling, security, uptime, and cost.
• Establish MLOps across the model lifecycle, the training pipelines, experiment tracking, model versioning, serving, and monitoring that take models from research into production and keep them healthy there.
• Make the model run in real time, with a low-latency inference and serving stack fast enough for a body to act while the world keeps moving.
• Get the model onto physical and digital agents, the runtime, tooling, and on-device and edge constraints of running on real hardware.
• Build the data infrastructure that turns unique, large-scale datasets into training-ready signal, working alongside the research and data teams.
• Shape technical strategy alongside research leadership, translating open research problems into systems that run.

What We’re Looking For

• Significant experience building and shipping large-scale systems, ideally ML or infrastructure-heavy, with a track record of taking hard systems to production.
• A track record of leading engineering teams, hiring, mentoring, growing engineers, and setting technical direction that people follow.
• Real technical depth, so you still read and write code and your judgment on hard systems problems is trusted.
• Strength across several of product engineering, MLOps, cloud operations, distributed training, real-time systems, and data infrastructure.
• A hands-on, builder mindset suited to an early-stage team, comfortable with ambiguity and a short loop from idea to shipped.
• The ability to balance speed and reliability, with the judgment to know which corners can be cut and which cannot.

Preferred Qualifications

• Experience scaling training or inference for large foundation models such as LLMs, diffusion, or multimodal systems.
• Real-time inference on the edge or on-device, where latency and compute budgets are tight.
• Deploying software onto physical hardware such as robots, embedded systems, or sensor-rich platforms.
• Data infrastructure and pipelines built for large-scale model training.
• Hands-on with cloud platforms and modern MLOps tooling for deploying, serving, and monitoring models in production.
• Experience as an early engineer or engineering leader at a startup that scaled, having stood up the org from a small base.
• A background that bridges research and engineering, having productionized research models before.

Tell us what you have built, what you have led, and how you make hard calls. We read everything.

Thespian Labs is an equal-opportunity employer. We hire for the work, and we want a lab full of people who don't all think alike. We sponsor visas for the right person.