Co-Op, Robot Perception & State Estimation

Linuxconfig; Cambridge (MA); On-site; USD 25,000 - 39,000; Full time

Job summary

Lila Sciences in Cambridge, MA, is seeking a Co-Op on the Production Robotics team to help build algorithms and software for robot state estimation, perception, and testing infrastructure. You will work on estimating position, localizing with AprilTags, and validating changes with CI before hardware deployment.

You will collaborate with robotics engineers, AI researchers, and software engineers to accelerate lab experiments and produce production-ready code for real robots.

Qualifications

• Pursuing Master’s or senior-year BS in Robotics, CS, or EE.
• Proficiency in Python and/or C++, with well-tested code experience.
• Familiarity with state estimation and sensor fusion.
• Strong foundation in linear algebra and probability.
• Comfort with Git and Linux development environments.
• Available for the full spring co-op term.

Responsibilities

• Build camera-based AprilTag and instrument detection and localization.
• Develop new robot capabilities in ROS 2 (Jazzy).
• Expand simulation-based tests and CI pipelines for validation before deployment.
• Evaluate estimation and perception performance on real robot data.
• Ship production code alongside robotics, software, and AI engineers.
• Document algorithms, test approaches, and integration patterns.

Skills

Python

C++

Robotics

Kalman filtering

State estimation

Git

Linux

Education

In-progress Master's in Robotics

Senior-year B.S. in CS/EE

Tools

OpenCV

ROS 2

Gazebo

CI

Job description

Cambridge, MA USA

As a Co-Op on the Production Robotics team at Lila Sciences, you will help build the algorithms and software that let our robots know where they are and what they are looking at, so they can run scientific workflows reliably inside the AI Science Factories (AISFs). The team develops the state estimation, perception, and testing infrastructure that general-purpose robotic skills depend on.

Your work will sit at the intersection of estimation, computer vision, and robotics software. You will help improve how our mobile bases estimate their position and motion, develop camera-based detection and localization of AprilTags and lab instruments, and strengthen the simulation-based testing and CI that validate changes before they reach hardware. Expect a mix of writing production-quality software, applying math to real sensor data, and debugging real-world behavior on physical robots.

You will work alongside robotics engineers, AI researchers, and software engineers, with day-to-day support from the Production Robotics team. The output is software that runs in production lab environments and directly accelerates the rate at which Lila can run experiments.

What You'll Be Building

• Build camera-based AprilTag and instrument detection and localization for robot manipulation and navigation
• Develop new robot capabilities in ROS 2 (Jazzy)
• Expand simulation-based tests and CI pipelines so changes are validated before deployment on hardware
• Evaluate estimation and perception performance on real robot data and contribute fixes back to the codebase
• Ship production code alongside robotics, software, and AI engineers
• Document algorithms, test approaches, and integration patterns for the rest of the team

What You'll Need to Succeed

• In-progress Master's (preferred) or strong senior-year Bachelor's in Robotics, Computer Science, Electrical Engineering, or a related field, with a controls/estimation leaning
• Proficiency in Python and/or C++, with coursework or project experience writing well-tested code
• Familiarity with state estimation and sensor fusion (e.g., Kalman filtering)
• Strong foundation in linear algebra and probability
• Comfort with Git and Linux development environments
• Strong communication skills and ability to work effectively across a multidisciplinary team
• Available for the full spring co-op term

Bonus Points For

• Experience with ROS 2 (Jazzy preferred) or another robotics framework
• Hands-on experience with camera systems and computer vision (e.g., OpenCV, AprilTags, camera calibration)
• Experience with simulation-based testing and CI (e.g., Gazebo, GitHub Actions)
• Experience integrating software with sensors, actuators, or other physical systems
• Coursework or projects in localization, SLAM, or robot control

About LILA

Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.

LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai.

Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply.

Lila Sciences iscommitted to equal employment opportunityregardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy .

A Note to Agencies

Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.