Senior AI Platform Engineer (Robotics)

Location: Bristol, United Kingdom

Company

hirify.global develops robotic systems and the software infrastructure that supports robot learning and deployment.

What you will do

• Design and build an end-to-end platform for robot data, model training, evaluation, versioning, release, and deployment.
• Create ingestion, processing, discovery, curation, labelling, quality-control, replay, and governance tools for multimodal robot data.
• Build distributed training, batch evaluation, regression, and release workflows using GPU clusters.
• Develop edge and robot deployment tooling, including packaging, optimization, staged rollouts, monitoring, and fleet-level model management.
• Improve platform reliability, observability, security, cost efficiency, and developer experience.
• Lead architecture decisions, write technical proposals, and mentor engineers in scalable ML systems practices.

Requirements

• Production experience building ML platforms, data-intensive systems, or distributed training infrastructure.
• Strong Python and software-engineering skills, including maintainable services, APIs, libraries, and workflow tooling.
• Experience with cloud infrastructure, containers, orchestration, Docker, and infrastructure-as-code.
• Knowledge of distributed storage and compute, large multimodal datasets, GPU workloads, PyTorch training, profiling, scheduling, and optimization.
• Understanding of reproducibility, data lineage, model registries, evaluation, deployment, monitoring, and rollback.
• A degree in computer science, engineering, or a related field, or equivalent practical experience, plus at least three years of relevant experience.

Nice to have

• Robotics or autonomous-systems data experience, including synchronized multimodal logs and time-series data.
• Distributed training at scale, cluster scheduling, checkpointing, fault tolerance, and experiment orchestration.
• Experience with imitation learning, reinforcement learning, active learning, or continual learning data engines.
• Edge inference and model optimization with ONNX, TensorRT, CUDA, or related technologies.
• Hybrid cloud and on-premise compute, fleet management, intermittent connectivity, security, privacy, or developer platforms.

Culture & Benefits

• Close collaboration with research, robot learning, perception, simulation, infrastructure, and field teams.
• Work includes operating production systems and converting recurring research and engineering friction into reusable platform capabilities.
• Occasional travel to partner or pilot sites may be required.
• Physical duties include prolonged desk and computer work and the ability to lift up to 30 lbs; reasonable accommodations may be available.