Applied Intuition
ML Runtime Optimization Engineer - Lead
Applied Intuition, Sunnyvale, California, United States, 94087
Applied Intuition is a vehicle intelligence company that accelerates global adoption of safe, AI‑driven machines. Founded in 2017 and now valued at $15 billion following its recent Series F funding round, Applied Intuition delivers the Vehicle OS, Self‑Driving System, and toolchain to help customers build intelligent vehicles and shorten time to market. Eighteen of the top twenty global automakers and major programs across the Department of Defense trust Applied Intuition’s solutions to deliver vehicle intelligence. Applied Intuition services the automotive, defense, trucking, construction, mining, and agriculture industries and is headquartered in Mountain View, CA, with offices in Washington, D.C., San Diego, CA, Ft. Walton Beach, FL, Ann Arbor, MI, London, Stuttgart, Munich, Stockholm, Bangalore, Seoul, and Tokyo.
Learn more at applied.co .
About the role We are looking for a lead software engineer with deep experience 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
Bring technical leadership to the ML model performance optimization team
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:
Bachelor’s in Electrical Engineering or Computer Science, OR B.Sc. in Computer Science, Mathematics, Physics or a related field
5+ years of experience with ML accelerators, GPU, CPU, SoC architecture and micro‑architecture
Strong software development skills with a focus on embedded programming
Experience profiling and optimizing model performance on embedded compute platforms
Experience working with deep learning frameworks (e.g., PyTorch, JAX, ONNX, etc.)
Nice to have:
M.Sc. or PhD in an 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, 401(k) 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: $199,295 – $264,500 USD annually.
Don’t meet every single requirement? If you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles.
Applied Intuition is an equal opportunity employer and federal contractor or subcontractor. Consequently, the parties agree that, as applicable, they will abide by the requirements of 41 CFR 60‑1.4(a), 41 CFR 60‑300.5(a) and 41 CFR 60‑741.5(a) and that these laws are incorporated herein by reference. These regulations prohibit discrimination against qualified individuals based on their status as protected veterans or individuals with disabilities, and prohibit discrimination against all individuals based on their race, color, religion, sex, sexual orientation, gender identity or national origin. These regulations require that covered prime contractors and subcontractors take affirmative action to employ and advance in employment individuals without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status or disability. The parties also agree that, as applicable, they will abide by the requirements of Executive Order 13496 (29 CFR Part 471, Appendix A to Subpart A), relating to the notice of employee rights under federal labor laws.
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Learn more at applied.co .
About the role We are looking for a lead software engineer with deep experience 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
Bring technical leadership to the ML model performance optimization team
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:
Bachelor’s in Electrical Engineering or Computer Science, OR B.Sc. in Computer Science, Mathematics, Physics or a related field
5+ years of experience with ML accelerators, GPU, CPU, SoC architecture and micro‑architecture
Strong software development skills with a focus on embedded programming
Experience profiling and optimizing model performance on embedded compute platforms
Experience working with deep learning frameworks (e.g., PyTorch, JAX, ONNX, etc.)
Nice to have:
M.Sc. or PhD in an 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, 401(k) 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: $199,295 – $264,500 USD annually.
Don’t meet every single requirement? If you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles.
Applied Intuition is an equal opportunity employer and federal contractor or subcontractor. Consequently, the parties agree that, as applicable, they will abide by the requirements of 41 CFR 60‑1.4(a), 41 CFR 60‑300.5(a) and 41 CFR 60‑741.5(a) and that these laws are incorporated herein by reference. These regulations prohibit discrimination against qualified individuals based on their status as protected veterans or individuals with disabilities, and prohibit discrimination against all individuals based on their race, color, religion, sex, sexual orientation, gender identity or national origin. These regulations require that covered prime contractors and subcontractors take affirmative action to employ and advance in employment individuals without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status or disability. The parties also agree that, as applicable, they will abide by the requirements of Executive Order 13496 (29 CFR Part 471, Appendix A to Subpart A), relating to the notice of employee rights under federal labor laws.
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