Lab Automation - Robotics Engineer

Xaira Therapeutics•South San Francisco, CA

2d•$150,000 - $180,000

About The Position

We are building a next-generation lab automation and robotics platform to transform how biological experiments are executed, monitored, and scaled. This platform will bring together robotic arms, mobile platforms, lab instruments, sensors, computer vision, workflow orchestration, and AI-enabled autonomy to increase the speed, reliability, reproducibility, and scale of experimental biology. As a Robotics Engineer, Lab Automation, you will help turn real scientific workflows into robust automated systems. You will work closely with biologists, chemists, automation engineers, software engineers, and robotics experts to understand manual laboratory processes and translate them into reliable robotic execution. This is a hands-on engineering role for someone who enjoys building, integrating, testing, and debugging physical systems. You will contribute to robotic manipulation, instrument integration, perception, task execution, simulation, and multi-station lab automation workflows. You will also have opportunities to grow into more advanced robotics, autonomy, and AI-enabled laboratory automation over time.

Requirements

Bachelor’s or Master’s degree in Computer Science, Robotics, Electrical Engineering, Mechanical Engineering, or related field.
Recent graduates with strong robotics, automation, hardware/software integration, or relevant project experience are encouraged to apply.
PhD candidates are welcome to apply, particularly if they are excited by hands-on robotic system building, integration, and lab automation.
Strong software engineering skills in one or more modern programming languages (e.g., Python, C++, C#), cloud-based workflows, and production software systems.
Familiarity with robotics software frameworks such as ROS2, MoveIt, or comparable tools.
Familiarity with computer vision, perception, motion planning, robotic manipulation, or sensor integration.
Comfort working with physical hardware, debugging real systems, and learning by doing.
Strong problem-solving skills, attention to detail, and ability to work across disciplines.
Ability to communicate clearly with scientists, automation engineers, software engineers, and robotics experts.

Nice To Haves

Experience with 6-axis robotic arms, autonomous mobile robots, grippers, machine vision systems, or automated material handling.
Experience with OpenCV, object detection, segmentation, tracking, pose estimation, SLAM, localization, or scene understanding.
Experience with Foxglove, Isaac Sim, MuJoCo, Gazebo, or other robotics simulation and debugging tools.
Experience integrating laboratory instruments such as liquid handlers, plate hotels, incubators, readers, and microscopes.
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 biological or chemical assays such as PCR, gel electrophoresis, DNA quantification, microscopy, high-throughput screening, or cell-based assays.
Experience with CAD, 3D printing, laser cutting, CNC machining, or rapid prototyping.
Exposure to GPU-accelerated inference (CUDA, TensorRT, ONNX), edge deployment, foundation models, reinforcement learning, imitation learning, behavior trees, autonomous task planning, or agentic robotics systems.

Responsibilities

Build, integrate, and maintain robotics software for robotic arms, mobile robots, sensors, grippers, and laboratory automation devices.
Develop motion planning, manipulation, perception, and safety logic for robotic systems operating in real laboratory environments.
Integrate laboratory instruments and devices through APIs, IoT interfaces, schedulers, and custom control software.
Help build task execution frameworks using state machines, behavior trees, planners, and recovery logic for autonomous or semi-autonomous lab workflows.
Benchmark and integrate computer vision methods for object detection, segmentation, tracking, pose estimation, localization, and scene understanding.
Create and use simulation or digital twin environments for motion validation, workflow testing, synthetic data generation, and system debugging.
Collaborate with scientists to translate biological and chemical workflows into automated protocols.
Support multi-station system integration, automated material handling, sample tracking, validation, logging, and error recovery.
Work hands-on with physical hardware to debug real systems, improve reliability, and iterate quickly.
Evaluate modern AI, autonomy, foundation-model, reinforcement-learning, or imitation-learning approaches where they can improve real robotic lab execution.