Senior Controls Engineer

About the Role

At Watney, Controls Engineers build the algorithmic foundations that make robots move. Your work will directly unlock a new class of robot capabilities with a uniquely high bar across precision, stability, and compliance while operating in unstructured environments such as warehouses, factories, and data centers.

As a Controls Engineer you'll own the entire estimation & controls stack: formulating the math, writing highly optimized code, tuning in the lab, and deploying across a growing fleet of robots operating at customer sites. You will also collaborate with research, hardware, and deployment teams to diagnose and correct failure modes and to design new features for both our robots and teleoperation interfaces.

We're looking for someone with technical rigor and sharp engineering instincts who is equally comfortable deploying to robots in production, not just simulation. You should be able to derive controller formulations on a whiteboard, reason about what can cause closed-loop instability, understand and navigate large codebases.

What You’ll Do

• Own the control stack end-to-end: design, implement, and tune low-level controllers (i.e. PID,H2/H-infinity) and optimal control schemes (i.e. MPC) making sure they run reliably and high frequencies. Among many things, these controllers will be used to augment our robots capabilities (e.g. multi-robot coordination) or to make our teleoperation interface as seamless and intuitive as possible.
• Own fleet controls metrics and guarantee its performance: evaluate and implement metrics that guarantee high-tracking accuracy and consistent behavior for all of our robots. This includes deploying adaptive-control and auto-tuning schemes to the entire fleet.
• Build our robots’ autonomous navigation capabilities: implement optimization and sampling based path planning while localizing and mapping the environment using onboard sensors.
• Close the loop with the field: partner with research, hardware, and deployment teams to diagnose real-world failures and translate them into more robust onboard behavior.

You May Be a Good Fit If You:

• Have hands-on experience implementing and tuning low-level controllers (PID, LQR, etc.) on real-world systems — not just in simulation.
• Have formulated and designed optimal and robust control algorithms (robust/stochastic MPC) and understand the tradeoffs between them.
• Have worked on manipulation systems and implemented: inverse kinematics, inverse dynamics (RNEA) and planning algorithms.
• Have worked with real-time, low-latency systems and are comfortable profiling and optimizing performance-critical code.
• Have worked with real-world sensors and built estimators, filters, and sensor-fusion pipelines.
• Have implemented localization and mapping algorithms (SLAM, UKF) for wheeled or legged robots.
• Have a strong mathematical foundation in linear algebra, calculus, and convex optimization.