Senior Machine Learning (Training Flywheel) Engineer

About the Job

We're partnered with a VC-backed start-up, founded by engineering leaders from Lyft & Google, that has raised $100M to become the category leader in multi-domain autonomy across air, land and sea. They have secured both defense and commercial contracts to deploy autonomous solutions at scale.

Role

As part of their growth plans they're looking to hire a Senior Machine Learning (Training Flywheel) Engineer to build their closed-loop training flywheel; turning raw fleet data into continuously improving models. The role will give you end-to-end ownership; covering data design → auto-annotation → training → evaluation → deployment pipelines. As well as implementing cutting edge VLM algorithms for auto-labeling & active learning loops.

What You'll Be Doing:

• Design the data → auto-annotation → training → evaluation → deployment loop
• Build scalable data ingestion and curation pipelines.
• Implement auto-labeling using VLMs and heuristics.
• Define evaluation protocols that correlate with on-ground performance.
• Drive active learning: select the right data.
• Integrate tightly with MLOps for continuous deployment.

The Ideal Candidate Would Have:

• Expertise with robotics/multi-modal data0 (camera, LiDAR, radar).
• Experience shipping perception or ML systems into production
• Auto-annotation techniques like VLM-based labeling.
• Large-scale data pipelines (Parquet, Arrow, object storage).

Salary

$180k-$250k

Location

Palo Alto, CA | Onsite (5 days)

This role will allow you to work on real-world deployed autonomy systems and own a critical layer of the ML stack for the forefront of AI + robotics!