Senior Software Engineer, ML Infrastructure (Robotics)

Location: Austin, TX, United States

Company

hirify.global is a human-centered robotics company developing AI-powered humanoid robots, including Apollo, for manufacturing, logistics, healthcare, and other applications.

What you will do

• Build self-serve ML platform APIs, workers, and control planes used by MLOps, Autonomy, Data Platform, and TeleOp teams.
• Develop data curation and annotation workflows for synchronized video, proprioceptive, tactile, and force-torque streams, including dataset versioning and lineage.
• Build multi-terabyte data transformation, dataset assembly, quality measurement, and GPU-serving pipelines.
• Create simulation and evaluation harnesses, benchmarks, metrics, and automated qualification gates for models before deployment to Apollo.
• Develop model storage and promotion workflows covering versioning, metadata, evaluation results, lineage, and ONNX/TensorRT packaging.
• Provide experiment tracking, training submission, sweep management, and reproducible container tooling while contributing to technical direction and mentoring engineers.

Requirements

• Production experience designing and shipping scalable platform services used daily by other engineering teams.
• Deep experience in at least one area: large-scale ML data pipelines, annotation and labeling, or evaluation and simulation.
• Strong Python and software engineering skills, including testing, API design, and code review.
• Experience with cloud infrastructure, Kubernetes, Docker, and modern CI/CD.
• 5+ years of professional software engineering experience in ML platforms, data infrastructure, or related fields, or 3+ years owning data and evaluation infrastructure for production models.
• Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related technical field, or equivalent experience.

Nice to have

• Robotics data formats and fleet-scale telemetry such as MCAP, ROS, or LeRobot.
• Simulation-in-the-loop evaluation with Isaac Sim, IsaacLab, or MuJoCo.
• Reinforcement or imitation learning infrastructure for embodied agents.
• ML model deployment to edge targets and robot fleets using ONNX Runtime or TensorRT.

Culture & Benefits

• Direct-hire position on a small, hands-on team.
• Close collaboration with Autonomy, Data Platform, and TeleOp.
• Regular participation in code reviews and design reviews, with responsibility for mentoring engineers.
• Work includes prolonged computer use, occasional lifting of up to 15 pounds, and the ability to communicate using vision, hearing, and speech.