ML Runtime Optimization Engineer
Applied Intuition · Sunnyvale
Roboticsonsitemid-level$215k–$315k
At a glance
Highlights
- Drive ML performance optimization for on-road and off-road ADAS/AD stacks.
- Optimize model inference efficiency and latency for customer compute boards.
- Profile models on embedded platforms to find and fix performance bottlenecks.
What they offer
- Equity in the form of options and/or restricted stock units
- Health, dental, vision, life and disability insurance
- 401k retirement benefits with employer match
- Learning and wellness stipends
- Paid time off
Ideal candidate
Embedded-minded engineer who loves squeezing maximum performance from ML models on real hardware. You enjoy profiling, collaborating with ML teams, and shipping efficient autonomy to production vehicles and robots.
Requirements
- Bachelors in Electrical Engineering or Computer Science, OR B.Sc. in Computer Science, Mathematics, Physics or a related field
- 3+ years of experience with ML accelerators, GPU, CPU, SoC architecture and micro-architecture
- Strong software development skills with the focus on embedded programming
- Experience profiling and optimizing model performance on embedded compute platforms
- Experience in working with deep learning frameworks (e.g., PyTorch, JAX, ONNX, etc.)
- remote policy
- In-office 5 days a week with occasional remote flexibility
Lab profile
About Applied Intuition
Builds simulation, vehicle OS, and autonomy infrastructure for automotive, defense, and heavy industries.
What they build
- Autonomy software stacks
- Vehicle operating systems
- Simulation and validation tooling
Known for
- Trusted by 18 of top 20 global automakers
- Expertise across automotive, defense, trucking, mining and agriculture
- Full-stack coverage from tooling to OS to autonomy
Key facts
- Founded in 2017
- Headquartered in Silicon Valley
- Valued at $15 billion
Posted · Last seen