Strong fit for systems-oriented engineers who build evaluation infrastructure and debug complex robotics workflows, working in logistics and manufacturing domains with a focus on simulation and real-world deployment.
Derived from job-description analysis by Serendipath's career intelligence engine.
Original posting from Maven Robotics via Greenhouse
About Maven
Maven Robotics designs, builds, and deploys intelligent robotics for logistics and manufacturing. Maven is building the first general-purpose robotics system for industrial work. Our mission is to activate autonomous labor at scale and build toward infinitely elastic industrial capacity. We’re a team of engineers, researchers, and operators who have spent our careers working on the hardest problems in AI, robotics, engineering, and autonomous systems. We work at the intersection of advanced research and real-world engineering, turning ideas into prototypes and deployed systems.
At Maven, we build around the realities of industrial work. The robots are designed from first principles for complex physical environments and rigorous commercial standards. They master real tasks that deliver immediate impact, industrial-grade reliability, and intelligence that compounds at scale. We’re growing an ambitious team of people who think in systems, move quickly, and are builders at heart.
About the Role
As a Robotics Evaluation Engineer at Maven Robotics, you will build the systems that measure, diagnose, and improve robot policy performance across simulation and real robots. You will own the core evaluation infrastructure that enables our AI team to rigorously compare models, understand failure modes, measure generalization and reliability, and make better decisions about data, training, and deployment.
You will work closely with robot learning researchers and engineers across simulation, perception, controls, data, and infrastructure to define task success, build reproducible evaluation frameworks, automate testing, and develop the tools needed to understand why robot policies succeed or fail.
What You’ll Do
Own the architecture, implementation, and evolution of Maven’s robot learning evaluation framework across simulation and real robots
Define task specifications, success criteria, failure taxonomies, evaluation metrics, and benchmark protocols for manipulation policies
Build automated systems for comparing models, detecting regressions, running large-scale evaluations, and generating clear performance reports
Develop simulation environments, task scenarios, and procedural variations used for policy evaluation
Build reproducible real-robot evaluation workflows that minimize manual supervision and produce statistically meaningful results
Measure and improve the relationship between simulated and real-world policy performance
Build tools for replaying, visualizing, and diagnosing policy failures across simulation and physical robots
Work closely with robot learning researchers to identify whether failures originate from the model, data, perception, controls, calibration, simulation, hardware, or long-horizon execution
What We’re Looking For
Significant experience building robotics evaluation, simulation, testing, or benchmarking systems.
Strong programming ability in Python, C++, or similar robotics or systems languages
Experience with robotics simulation platforms such as Isaac Sim, MuJoCo, Gazebo, or similar systems
Experience evaluating learned robotic policies in simulation and on physical robots
Experience designing reproducible experiments, metrics, benchmarks, and failure-analysis workflows
Ability to build reliable software systems for automated testing, data collection, visualization, and reporting
Strong understanding of robotics systems and the ability to debug issues across software, models, sensors, controls, and hardware
A track record of independently owning complex technical projects from initial design through deployment and ongoing operation
Nice to Have
Familiarity with sim-to-real transfer, domain randomization, sensor modeling, and system identification
Experience importing and configuring simulation assets, including robot models, objects, joints, collisions, inertial properties, materials, and sensors
Experience with hardware-in-the-loop testing, continuous integration for robotics, or automated robot test cells
Familiarity with multimodal robot policies, vision-language-action models, or other learned manipulation architectures
Strong background in statistical analysis, confidence estimation, and experimental design
Equal Opportunity
Maven Robotics is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.