Robotics Software Engineer

Eka Robotics

Eka Robotics is on a mission to build intelligence for the physical world - robots that are fast, general, and reliable. Our approach, grounded in physics, unlocks superhuman capabilities. We are defining the frontier of robotics research and deployment.

Our team consists of pioneers in robotics and machine learning. We are now hiring to scale our R&D effort. We are looking for hands-on individuals who are excited to help shape the future of robotics.

Responsibilities

Stack Optimization: Maintain a deep understanding of the full robotics software stack; profile and optimize data flows to minimize end-to-end latencies across components.

Observability & Diagnostics: Design and implement logging and monitoring frameworks to facilitate rapid debugging and provide visibility into system dataflows.

Testing & Health Monitoring: Develop testing suites and validation pipelines specifically designed to identify robot degradation and anomalies.

System Identification: Design and execute experiments for system identification to refine simulation models and controller performance.

ML Deployment & Developer Experience : Build streamlined deployment systems for machine learning models, prioritizing intuitive tooling that simplifies prototyping and minimizes friction for research teams.

Production-Level C++/python: Author and maintain high-performance, production-grade C++ codebases adhering to industry best practices, and use Python for tooling, data analysis, and scripting.

Performance & Scalability: Proactively identify bottlenecks in performance and scalability, driving iterative enhancements to the software architecture.

Safety Integration: Design and implement safety functions while ensuring their compatibility with machine learning models.

Minimum Qualifications

Education: BS, MS or higher in Computer Science, Robotics, Computer Engineering, or a related technical field.

C++ Expertise: 3+ years of professional experience writing production-quality C++, with a focus on memory management, multi-threading, and real-time constraints.

Robotics Frameworks: Hands-on experience with ROS2 or similar robotic middleware, including custom message generation and lifecycle management.

Systems Engineering: Strong understanding of Linux systems, including profiling tools to identify and resolve latency bottlenecks.

ML Deployment: Experience deploying and optimizing machine learning models (TensorRT, ONNX) onto edge devices or robotic platforms.

Preferred Qualifications

Safety Critical Systems: Experience implementing safety functions or working with functional safety standards.

Math & Physics: Strong foundational knowledge of system identification, control theory, and rigid body dynamics.

Infrastructure & DevOps: Experience building automated testing pipelines, CI/CD for hardware, and custom logging/telemetry/visualization stacks.

Simulation: Proficiency in using simulation environments for system validation and testing.