Software Engineer, Robotics

Integrated Biosciences, Inc.•Redwood City, CA

1d•$140,000 - $230,000•Onsite

About The Position

Integrated Bio is a physical AI company developing multimodal biological datasets and AI for drug discovery, with a focus on aging and age-related diseases. The company is building a closed-loop discovery engine that connects AI-generated hypotheses, high-throughput experiments on living systems, and feedback from experimental results to improve its models. This is a software engineering role with a robotics mandate. The role primarily involves building systems—including data pipelines, services, interfaces, evaluation harnesses, and the control and learning stack for a robotic manipulation station. The engineer will also own the station’s hardware, from mounting and calibration through deployment, and contribute to application and infrastructure code. Integrated Bio is open to a range of experience levels, from strong master's graduates with portfolios of built work to senior robotics engineers. The position is onsite at Redwood LIFE in Redwood City, California. Visa sponsorship is available where applicable. The search is underway from October to December 2026, with a target start date between December 2026 and February 2027. Compensation is $140,000–$230,000 depending on experience and level, plus substantial equity and a performance bonus.

Requirements

Strong software engineering fundamentals, including architecture, version control, testing, deployment, and building systems others can run.
Experience building full-stack systems, from databases and backend infrastructure to user interfaces.
Experience shipping robot software for manipulation, motion planning, control, or learned policies, using ROS/ROS2 or an equivalent defensible stack.
Ability to provision, deploy, and manage cloud resources, such as Docker, AWS, and bare metal.
Fluency in using AI coding tools such as Claude Code, Codex, and Grok to build software quickly.
Comfort with hardware work, including mounting, wiring, calibration, and debugging robots.
A bachelor's, master's, or doctoral degree in computer science, robotics, electrical or mechanical engineering, or a related field.
A portfolio of systems built from scratch through working deployment, ideally with video.
Judgment to determine what to build next without direct instruction.

Nice To Haves

Practical experience with imitation learning, including behavior cloning, diffusion policies, ACT, or vision-language-action models.
Experience with teleoperation rigs, VR controllers, or other demonstration-collection systems.
Experience with simulation and sim-to-real transfer, such as MuJoCo, Isaac Lab, or similar tools.
Familiarity with Postgres, TypeScript, React, and modern backend and frontend frameworks.
Experience building infrastructure and tooling around AI processes and agents, such as post-training, MCP servers, skills, automations, or harnesses.
Experience with laboratory automation, such as liquid handlers, plate readers, SiLA, OPC UA, or scheduling software.
Experience with multimodal data, video pipelines, or large-scale data capture.
Curiosity about biology.

Responsibilities

Build software systems used by scientists, including data infrastructure, services, APIs, and interfaces.
Build a teleoperation and data-capture pipeline that turns demonstrations and routine lab work into clean, labeled training data.
Own the robotic manipulation station end to end, including dexterous manipulators, depth cameras, and VR teleoperation, from mounting and calibration through the control stack.
Train, evaluate, and deploy manipulation policies for laboratory tasks such as liquid handling and plate manipulation, and establish success metrics.
Set up simulation for the robotic station so policies can be developed and stress-tested before use on hardware.
Integrate the robot and its data into the broader AI agent harness.
Automate experimental workflows in collaboration with scientists and measure the resulting time savings.
Work across the general engineering stack, including scientist tooling, internal applications, pipelines, and cloud infrastructure.