Robotics Software Engineer

About Terabase Energy Terabase Energy builds the automation and robotics systems that are transforming how utility‑scale solar power plants are built. Our platforms combine robotics, controls, and software to increase construction speed, quality, and safety across the solar EPC lifecycle. As physical automation becomes central to how we deliver projects, we are building out a Physical AI capability that pairs machine perception and decision‑making with the mechanical and controls systems already deployed in the field. Job Description We are hiring an AI Engineer to embed with our mechanical and controls engineering teams and implement physical AI: systems where computer vision and machine learning models perceive the physical world and drive real automation and mechatronic action. This is a hands‑on, cross‑disciplinary role focused on two outcomes — using AI vision to improve manufacturing and construction process performance, and using AI vision for automated material and component quality control (QC). This position reports directly to our Director of Factory Automation and will work very closely with the controls and mechanical engineering teams. You will work at the intersection of ML models, sensors, and actuated hardware — not in a research silo. Success means AI systems that reliably run on real equipment, in real production and field environments, and materially move throughput, yield, and quality metrics. Our systems run on production floors and active solar construction sites, not in a lab. A critical requirement of this role is building AI systems that are supportable and robust to real‑world deployment conditions — dust, heat, cold, vibration, moisture, and intermittent connectivity — and that a field team can operate, monitor, and troubleshoot without a machine‑learning background. We're looking for an engineer with a proven track record shipping real‑time automated systems into production — someone who has owned a system end‑to‑end across controls, perception, and the software layer that ties them together, not just a component of one. Successful candidates will exhibit strong resourcefulness, analytical thinking/problem solving, excellent communication skills, and adaptability all coupled together by a superlative work ethic. Most importantly, you, like us, will be dedicated to accelerating the decarbonization of the global economy using digital and automation technology to further reduce the cost of utility‑scale solar. Responsibilities Partner closely with the Controls and Mechanical Engineering teams on automated work cells, PLC‑controlled systems, and end‑effector tooling — owning the full loop from real‑time control and perception through the operator‑facing software that runs on the equipment Engineer AI/vision systems to be robust and supportable in outdoor, active solar‑construction environments — accounting for dust, temperature extremes, vibration, moisture, and intermittent connectivity — and maintainable by field personnel without ML expertise Design, train, and deploy computer vision models (object detection, defect/anomaly detection, segmentation) for real‑time material and component QC on automated assembly and production lines Build perception pipelines that fuse camera, LiDAR, and other sensor data, and deploy low‑latency inference at the edge (e.g., NVIDIA Jetson or similar) to support closed‑loop equipment control and real‑time vision‑guided actions Develop and validate defect‑classification and QC models against production tolerances — including comprehensive model and system testing — working with manufacturing and quality engineering to define acceptance criteria Collect, label, and manage training data from factory and field environments; build the data pipelines and tooling needed for continuous model improvement Instrument automated cells and production lines with the telemetry needed to evaluate AI system performance, uptime, and impact on cycle time, scrap rate, and yield Build lightweight operator‑facing tools — dashboards, web UI — so field teams can monitor and interact with AI‑enabled systems without ML expertise Support integration, commissioning, and on‑site troubleshooting of AI‑enabled automation equipment in test and production environments, working closely with controls engineers, and document system performance and failure modes for cross‑functional stakeholders Support risk assessment and EHS review of newly designed AI‑enabled machines, ensuring compliance with safety protocols Minimum Qualifications Bachelor's degree in Computer Science, Electrical Engineering, Mechanical Engineering, Robotics, or a related field 5+ years of hands‑on experience shipping automated, mechatronic, or robotic systems into production — spanning real‑time control, perception, and the software that connects them Proficiency in Python and computer vision tooling (OpenCV or equivalent); experience with deep‑learning frameworks (PyTorch, TensorFlow) is a plus but not required Working understanding of how AI perception connects to physical systems: sensors, actuators, motion control, PLCs, or robotic arms and end effectors Experience with robotic middleware (ROS/ROS2) and/or industrial communication protocols (EtherCAT, EtherNet/IP, CAN, Modbus) Demonstrated experience designing systems for reliability and supportability in harsh, uncontrolled, or outdoor environments (construction, industrial field equipment, automotive, aerospace, or similar) — not just lab or data‑center conditions Willingness and ability to travel up to 30% Prefer experience in industrial manufacturing and/or construction industry Self‑starter, able to thrive in a fast‑paced and continually changing environment. Strong communication, customer relationship skills, and ability to communicate effectively and interact within a team environment. Proven skill in MS Suite of software (Outlook, Excel, PowerPoint, etc.) Preferred Qualifications Experience with industrial machine vision systems (e.g., Cognex, Keyence) or camera/lighting setup for QC applications Experience with edge AI deployment tooling (TensorRT, Jetson, or similar embedded inference platforms) Use of robotic simulation software (e.g., KukaSim, Roboguide, Visual Components, NVIDIA Isaac Sim, Gazebo) for sim‑to‑real workflows and offline testing Exposure to reinforcement learning, imitation learning, or vision‑language‑action (VLA) / generalist robot policy models Experience taking an AI‑enabled product from concept to shipped, including the software layer around it (web UI, APIs, data pipelines) Compensation And Benefits Our salary ranges are determined by role, level, and location. This role offers a base salary of $130,000 – $160,000. Within each posted range, individual pay is determined (and may be greater or higher), dependent on work location and additional factors, including job‑related skills, experience, and relevant education or training. Terabase offers competitive compensation along with a comprehensive benefits package, including: Generous time off and holiday policy Flexible time off Comprehensive benefits package Career progression 401k match Stock options Home office set up allowance And much more! Travel: Significant travel to customer and project sites. Terabase is an equal opportunity employer. We recruit, hire, employ, train, promote, and compensate individuals based on job‑related qualifications and abilities. We strongly encourage people of all backgrounds to apply. We do not discriminate for any reason including race, color, sex, gender, age, religion or religious creed, national origin, ancestry, citizenship, marital status, sexual orientation, gender identity, gender expression, genetic information, physical or mental disability, military/ veteran status, or any other characteristic protected by law. We offer a welcoming and inclusive environment in service to one another, our products, the diverse consumers we represent, and the communities we call home. Principles only. This role is not open to receiving agency candidates, and any contingent submissions will not be considered. Terabase Energy does not utilize third‑party recruitment agencies. Please contact our Recruiting team at View email address on click.appcast.io with any staffing‑related inquiries. #J-18808-Ljbffr