Software Engineer, Data Platform

About Mind:

Mind Robotics is building robots that learn from real-world experience, and the data platform is what turns raw experience into training signal. Every day, sensor data flows in from multiple sources — arriving in different formats, at different volumes, and with different quality bars. This team owns what happens next: ingesting that data reliably, validating and curating it for quality and diversity, powering annotation, and building the automated methods that will increasingly do that labeling work.

About the role:

As a Software Engineer working on the data platform, you'll be one of the founding engineers on the team that owns our application layer, reporting to our Head of Application Engineering. The systems work today; your job is to help harden and productionize them for scale — ingesting from a growing number of sources and field sites, and turning raw captures into training-ready data faster and at higher quality. This is early, hands-on, 0-to-1 engineering: you'll build the pipelines and tooling that determine what data actually makes it into our models, and see the effect on robot behavior.

You will:

Build data ingestion pipelines from multiple sources, including our own field capture and teleop stacks

Build automatic data validation systems that catch quality issues before data reaches annotation or training

Build and improve annotation ingestion, tooling, and workflows to increase labelling efficiency and throughput

Own data quality and diversity — build the systems and metrics that tell us what data we have, what's missing, and where to focus collection

Explore and build automated annotation methods, including running computer vision and vision-language models for tasks like depth estimation, hand tracking, and auto-labeling, to reduce manual labelling load over time

Support the platform — debug issues in live pipelines, instrument for observability, and work directly with research and annotation partners who depend on your software

Requirements:

2+ years of software engineering experience building production systems

Strong programming fundamentals and comfort working across the stack — services, data pipelines, and applied ML tooling

Experience with at least one of: real-time or large-scale data pipelines, ML data workflows, computer vision, or data infrastructure

Bias for ownership: you've taken features or systems from prototype to production and supported them in the field

Clear communication and close collaboration with product, research, and annotation/operations partners

Hands-on experience with sensor data (video, depth, IMU, force/torque) and the infrastructure to process, validate, and label it at scale is a plus

Experience with streaming or near-real-time data pipelines is a plus

Familiarity with ML data workflows (datasets, labelling, evaluation) is a plus

Experience running or integrating computer vision or vision-language models (e.g., depth, pose/hand tracking, open-vocabulary detection, auto-labeling) is a plus