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Kodiak Robotics, Inc. was founded in 2018 and has become a leader in autonomous ground transportation committed to a safer and more efficient future for all. The company has developed an artificial intelligence (AI) powered technology stack purpose-built for commercial trucking and the public sector. The company delivers freight daily for its customers across the southern United States using its autonomous technology. In 2024, Kodiak became the first known company to publicly announce delivering a driverless semi-truck to a customer. Kodiak is also leveraging its commercial self-driving software to develop, test and deploy autonomous capabilities for the U.S. Department of Defense.
We are seeking a highly skilled Senior AI Acceleration Engineer to join our AI/ML team. In this role, you will be responsible for optimizing and accelerating machine learning models for deployment on embedded hardware platforms.
In this role, you will:
- Optimize and accelerate ML models for embedded hardware using techniques such as quantization, pruning, knowledge distillation, model compression, and hardware-specific optimizations
- Develop high-performance custom kernels using CUDA, OpenCL, or other low-level programming tools to accelerate computations and implement efficient algorithms
- Leverage and customize inference optimization frameworks like TensorRT, TVM, or ONNX Runtime to maximize performance on target platforms
- Profile and analyze model performance, identify bottlenecks, and implement solutions to improve computational efficiency and reduce latency
- Collaborate with cross-functional teams, including hardware engineers and software developers, to co-design software and hardware solutions that maximize overall system performance.
Qualifications:
- BS, MS, or PhD with academic or at least 2-3 years of industry experience in optimizing and accelerating machine learning models for embedded systems
- You are a skilled software engineer with experience in Python, C++, CUDA programming, and strong problem-solving skills
- You are passionate about pushing the boundaries of ML performance on hardware and have ideally worked on embedded platforms or autonomous systems before
- You also have a strong knowledge of low-level kernel development and experience with ML optimization techniques such as quantization, pruning, model compression, and knowledge distillation
What we offer:
- Competitive compensation package including equity and biannual bonuses
- Excellent Medical, Dental, and Vision plans through Kaiser Permanente, Anthem, and Guardian (including a medical plan with infertility benefits)
- Flexible PTO and generous parental leave policies
- Our office is centrally located in Mountain View, CA
- Office perks: dog-friendly, free catered lunch, a fully stocked kitchen, and free EV charging
- Long Term Disability, Short Term Disability, Life Insurance
- Wellbeing Benefits - Headspace, One Medical, Gympass, Spring Health
- Fidelity 401(k)Commuter, FSA, Dependent Care FSA, HSA
- Various incentive programs (referral bonuses, patent bonuses, etc.)
The annual salary range for this full-time position is $150,000-$250,000 + bonus + equity + benefits. Actual salary ranges will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Please note that the compensation details listed above are base salary only and do not include bonus, equity, or benefits.
At Kodiak, we strive to build a diverse community working towards our common company goals in a safe and collaborative environment where harassment of any kind is strictly prohibited. Kodiak is committed to equal opportunity employment regardless of race, ethnicity, religion, gender identity, sexual orientation, age, disability, or veteran status, or any other basis protected by applicable law.
In alignment with its business operations, Kodiak adheres to all relevant statutes, regulations, and administrative prerequisites. Accordingly, roles that carry more sensitive requirements may be limited to candidates that can satisfy additional scrutiny and eligibility for such positions may hinge on verification of a candidate’s residence, U.S. person status, and/or citizenship status. Should the position require, and Kodiak determines that a candidate’s residence, U.S. person status, and/or citizenship status necessitate an export license, bar the candidate from the position, or otherwise fall under national security-related restrictions, Kodiak will consider the candidate for alternative positions unaffected by such restrictions, under terms and conditions set forth at Kodiak’s sole discretion, or, as an alternative, opt not to proceed with the candidate’s application. If applicable, Kodiak may provide visa sponsorship for eligible candidates.
Kodiak Robotics Mountain View, California, USA Office
1045 Terra Bella Ave, Mountain View, CA, United States, 94043
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
