Software Engineer, Robotics

Deccan AI is a model training and evaluation startup (Mountain View, CA; delivery center in Hyderabad). Founded by IIT Bombay, IIM Ahmedabad, and ex-Google alumni and backed by Prosus Ventures, we build expert-curated datasets and evaluation infrastructure for frontier AI labs including Google DeepMind and Snowflake. Our Physical AI practice is building the data backbone for embodied AI — annotation, synthetic data generation, and model evaluation that help robots learn manipulation and reasoning at scale.

VLA (Vision-Language-Action) foundation models need more than research breakthroughs — they need production software that connects data pipelines, simulation, training loops, and evaluation into a reliable system. You'll build that system. This is not a pure ML research role or a data engineering role — it sits at the intersection, where you write the code that makes VLA training work end-to-end. You'll work directly with frontier lab clients and ship systems used to train the next generation of robot foundation models.

Build the VLA training integration layer — data loaders, format converters, and preprocessing that feed curated datasets (real + synthetic) into training frameworks (LeRobot, Octo, OpenVLA, π0).

Develop evaluation and benchmarking infrastructure: sim-based rollouts in Isaac Lab, success-rate tracking, regression detection, and automated reporting for client delivery.

Own dataset management — versioning, schema validation, metadata indexing, and format conversion across Open X-Embodiment, LeRobot HDF5, RLDS, and client-specific formats.

Implement sim-to-real transfer tooling: domain randomization configs, Cosmos Transfer integration, and quality validation ensuring synthetic data improves policy performance.

Build annotation platform backend systems — task taxonomy APIs, temporal segmentation, quality scoring, and inter-annotator agreement for robotics episode data.