Key skills
C++PythonBackend programmingData structuresAlgorithmsSoftware architectureDesign patternsReal-time software systemsML model deploymentModel versioningData pipeline managementROS2Simulation toolsCARLACAIMLHelmCommunicationCollaboration
About this role
Helm.ai builds AI software for autonomous driving and robotics, focusing on making autonomous technologies more efficient and accessible. They are seeking versatile engineers to shape core components of their autonomous stack, with responsibilities that include designing, implementing, and testing vehicle software/hardware systems.
Responsibilities:
- Design, develop, and deliver safe, scalable, and robust real-time software for mass production grade autonomous vehicle systems directly contributing to safer roads and economically viable AI deployment
- Conduct in-depth algorithm analysis, optimization, and iteration to enhance efficiency and accuracy across the AV stack
- Architect scalable continuous learning system for deploying new ML models, monitoring their performance, and prioritizing improvements
- Collaborate with platform, embedded, and AI teams to ensure cohesive development, validation, and integration of ML based perception, prediction, and planning
- Stay abreast of industry trends and emerging tools in high-performance computing, real-time systems, and AI-driven mobility
Requirements:
- Bachelor's or Master's degree in Computer Science, Electrical Engineering, Robotics; Ph.D. preferred
- Demonstrated ability to lead projects, mentor team members, and work autonomously in high-stakes fast-paced environments
- Strong foundation in backend programming (C++, Python) and proven track record in designing, developing, and deploying performant and/or real-time software systems, e.g. aerospace, online ads, robotics, gaming, high-frequency trading
- Strong command of data structures, algorithms, software architecture, and design patterns
- Excellent problem-solving, communication, and collaboration skills, with a passion for innovation
- Experience in autonomous vehicle development, with expertise in software/hardware integration
- Experience with ROS2 or other robotics middleware
- Experience with ML model deployment and monitoring in production environments, including data pipeline management and model versioning for safety-critical systems
- Expertise in simulation tools (e.g., CARLA) and real-world testing protocols for autonomous vehicles