Jobs at Medra

Own end-to-end customer deployments of a Physical AI robotics platform. Translate scientific workflows into technical requirements, integrate robots, instruments, and software, and build, test, debug, and deploy production workflows. Work directly with customers and forward-deployed scientists during site bring-up and validation, diagnose cross-system failures, extend integrations, and generalize deployment learnings into reusable platform capabilities. The role is fully in-person in San Francisco and requires approximately 30% travel.

Paid Winter 2026 mechanical engineering internship focused on building scientific automation tools. Responsibilities include designing components, producing drawings, building assemblies, debugging hardware, testing and scaling hardware, selecting materials, and applying manufacturing techniques. Candidates should be hands-on, comfortable with rapid prototyping, and able to work across disciplines. Robotics, mechatronics, circuit design, PLM systems, and robotics programming experience are preferred.

Own end-to-end interview scheduling, candidate walk-ins, on-site logistics, and candidate experience. Manage Ashby workflows, pipelines, reporting, automations, and data integrity. Use AI tools to streamline recruiting tasks, communications, sourcing, screening, and insights. Partner with recruiters and hiring managers to keep requisitions on track while managing multiple calendars and priorities in a high-volume, on-site environment.

Develops post-training recipes and data pipelines for AI models, creates evaluations, builds agentic systems with custom tools, and integrates reasoning capabilities into live scientific workflows. The role collaborates with scientists, robotics engineers, and operations teams to improve experimental design and assay development while shaping the technical direction of a new machine learning team.

Maintain robot uptime and reliability for daily protocol runs, diagnose and resolve operational issues onsite, perform preventive maintenance and calibrations, monitor system health with dashboards and alerts, document incidents and resolutions, support engineering visits and validate deployments, and coordinate schedules with customer scientists.

Design, build, and maintain full-stack tools and internal systems to operate autonomous lab robots. Ship end-to-end features across React frontends, Node and Python services, and AWS infrastructure. Collaborate with scientists, operations, and robotics engineers to integrate AI-driven workflows and improve experiment design, monitoring, and analysis.

Design and implement robotics software for lab automation, including motion planning, collision avoidance, vision for consumables, simulation and on-robot integration, and collaborate with partner scientists to deploy scalable, robust solutions.

The Mechanical Engineer will design, test, and implement hardware for robotic automation, requiring testing and iteration on mechanical systems and CAD designs.

As a Tech Lead Manager, you will oversee full-stack systems development, mentor engineers, and make key architectural decisions while contributing code directly.