ML Runtime Optimization Engineer
Join Applied Intuition as an ML Runtime Optimization Engineer to optimize ML models for embedded environments in a collaborative team.
Posted by employer 1 year ago
First seen on Joblaze 1 month ago
Last verified on the company career page 1 day ago
Requirements
- Experience
- 3+ years
- Education
- Bachelor's degree
Not disclosed in this posting: compensation, visa sponsorship.
Benefits
Joblaze summary
The ML Runtime Optimization Engineer at Applied Intuition focuses on enhancing the performance of machine learning models for embedded systems, specifically targeting advanced driver-assistance systems (ADAS). This role requires expertise in deep learning frameworks and embedded programming, with a strong emphasis on optimizing model inference efficiency and latency. Ideal candidates possess a background in electrical engineering or computer science, along with several years of experience in ML accelerators and performance profiling. The position is situated within a rapidly growing company that is at the forefront of physical AI technology.
Joblaze insights
Quick facts
- Is the ML Runtime Optimization Engineer role remote?
- No — this is an on-site role in Sunnyvale.
- How much experience is required?
- At least 3 years of relevant experience for this ML Runtime Optimization Engineer role.
- Where is the role based?
- Applied Intuition is hiring for this position in Sunnyvale.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: CUDA, JAX, ONNX, PyTorch, TensorRT, Triton.
- What seniority level is this role?
- Applied Intuition targets mid-level candidates for this position.
- Is this full-time or contract?
- Full-time for this ML Runtime Optimization Engineer role at Applied Intuition.
From the original posting
About the role
We are looking for a software engineer with deep experience in optimizing ML models and deploying them on production-grade embedded runtime environments. You’ll work across the entire ML framework stack (e.g. PyTorch, JAX, ONNX, TensorRT, CUDA, XLA, Triton).
At Applied Intuition, you will:
Drive ML performance optimization on multiple technologies for on-road and off-road ADAS / AD stacks targeting deployment on a variety of embedded compute platforms
Develop compute usage strategies to optimize efficiency and latency of model inference for compute boards selected by our customers
Work on model pruning and quantization, and support deployment on memory constrained platforms
Collaborate closely with ML engineers and software developers on technical efforts to find and optimize efficient model architecture solutions
Set up methodologies to profile the model performance on target embedded compute platforms and identify performance bottlenecks as part of stack integration
We're looking for someone who has:
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.)
Nice to have:
M.Sc or PhD in a ML related area
Built an ML optimization framework from scratch before
Deployed ML solutions to embedded chips for real time robotics applications
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.
Standard company text repeated across Applied Intuition's postings is omitted here.
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