About the role

Applied Intuition builds autonomy software deployed on real vehicles across multiple continents - passenger cars, trucks, mining vehicles, and defense platforms. The business is profitable, growing fast, and deeply embedded with OEMs globally.

We are looking for an Engineering Manager to own the data and evaluation layer that powers our E2E autonomy models. This role covers what the industry typically staffs as separate orgs: data enrichment and autolabeling, dataset curation and corpus management, evaluation and metrics infrastructure, and the closed-loop systems that connect on-road performance back to training. Here it's one org under one leader, serving ADAS, L4 trucking, mining, and off-road from a common pipeline.

Model iteration speed is gated by how fast you close the loop. This team owns the pace. You will be hands-on in the technical decisions and close enough to the models to know when something is off.

At Applied Intuition, you will:

• Own data enrichment: the ML pipelines that produce semantic labels, object annotations, behavior tags, and derived features at petabyte scale across cameras, lidar, and radar. Ensure enrichment quality keeps pace with model requirements as they evolve.

• Build the curation and corpus management systems: distribution analysis, targeted mining for long-tail scenarios, embedding-based data selection, scenario diversity and geographic balance enforcement.

• Own evaluation from offboard metrics to on-road driving quality. Define the metrics, benchmarks, and regression tests that determine whether a model ships. Close the sim-to-real gap. Build "eval of eval" tooling to measure and improve the evaluation system itself.

• Recruit, develop, and technically lead the team. Build a culture of rigor on a safety-critical system.

We’re looking for someone who has:

• 5+ years building ML or data systems for robotics or production software systems.

• 2+ years managing or technically leading engineering teams.

• Experience with large-scale data pipelines: ingestion, curation, and processing of large-scale multi-modal sensor data.

• Experience reasoning about dataset composition, distribution balance, and corpus-level quality - making data decisions that measurably improved model performance.

• Strong software engineering in Python; comfort with C++ and distributed systems.

Nice to have:

• Shipped perception, prediction, or planning models to production vehicles.

• Experience with state-of-the-art simulation for ML eval (e.g. neural rendering and simulation).

• Labeling and auto-labeling pipelines: automated pre-labeling, quality verification, human-in-the-loop workflows.

• RL and reward engineering for autonomous driving or robotics.

Compensation at Applied Intuition for eligible roles includes base salary, equity, and benefits. Base salary is a single component of the total compensation package, which may also include equity in the form of options and/or restricted stock units, comprehensive health, dental, vision, life and disability insurance coverage, 401k retirement benefits with employer match, learning and wellness stipends, and paid time off. Note that benefits are subject to change and may vary based on jurisdiction of employment.

Applied Intuition pay ranges reflect the minimum and maximum intended target base salary for new hire salaries for the position. The actual base salary offered to a successful candidate will additionally be influenced by a variety of factors including experience, credentials & certifications, educational attainment, skill level requirements, interview performance, and the level and scope of the position.

Please reference the job posting’s subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the location listed is: $255,700 - $346,000 USD annually.