San Francisco; Toronto · 7 months ago
You will develop and advance the multimodal vision, language and action models that power LeLamp's perception and behavior, owning work from research through deployment on real hardware. You will also integrate ML systems with robotic hardware and collaborate with robotics engineers.
Human Computer Lab is a research lab building character robots that feel alive and responsive. Our first robot, LeLamp, explores a new category of consumer robotics where everyday objects become interactive and help us reshape our attachment to technology. Our goal is to push the frontier of human-robot interaction by making technology more legible, emotionally intuitive, and human-centered. We are building the foundation for a new generation of robots designed for everyday environments. What to expect This role is for a machine learning engineer who wants to work on the models that give LeLamp its intelligence – the systems that let the robot perceive its environment, understand what's happening around it, and respond in ways that feel natural and intentional. You'll be developing and advancing the multimodal model architectures at the core of our robot, spanning vision, language, and action, and owning that work from early research through to deployment on real hardware. This is not a role where you train models in isolation and hand them off. You'll see your work running in the robot, shaping how it behaves in the world. You'll work closely with the research and mechanical team at the frontier of embodied AI, where the problems are genuinely open and the decisions you make directly shape what the robot can do. In this role, you will: • Develop software systems for robotic platforms that power robot perception, intelligence, and behavior • Write maintainable, production quality code for research and deployment • Build multi-modal machine learning models for tasks such as computer vision, audio processing, and interaction understanding • Design and implement pipelines for training and deploying machine learning models • Integrate ML systems with robotic hardware and embedded systems • Improve robot perception, responsiveness, and behavioral intelligence • Collaborate with robotics engineers to build integrated robotic controls and architectures You may be a good fit, if you: • 3+ years (or equivalent) working on machine learning for robotics, controls, or perception • Have strong programming skills in Python and/or C++ and understanding of algorithms and software engineering fundamentals. • Have experience with machine learning frameworks such as PyTorch • Have experience in one or more of the following areas: computer vision, robotics, reinforcement learning, or multimodal AI • Have experience building and deploying machine learning systems preferably in Simulations (Issac Sim, MJLab, Mujoco, etc.) • Show intentionality in design decisons and feel ownership over outcomes, even for systems you don't own. • Think holistically about the entire system and approach complex problems with creative, outside-the-box solutions. You will be a strong fit, if you: • Absolutely love and are passionate about building intelligent physical systems. • Move quickly and can do rapid iteration cycles. Share work early and iterate. • Take ownership over the systems they design and build, and are curious, resourceful, and motivated to solve difficult problems. • Work well in small, collaborative teams. • Consider not just what immediately works, but how the consumer will engage with the robot. The early team becomes the DNA of the company. We set ourselves and others to a high standard, and we respond with kindness when things get hard but keep everyone accountable. This requires us to be curious, creative, and diverse in our thinking and approach. We’re proud to be an equal opportunity employer and consider all qualified applicants regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. Even if you don’t meet every single requirement, we encourage you to apply. Studies show that women and underrepresented groups often hold back unless they meet 100% of the criteria - we don’t want that to be the reason we miss out on great talent.
Posted Apr 1, 2026
