Staff Machine Learning Engineer - Deployment at Kodiak Robotics – San Francisco Bay Area | Jobyssey

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.

Kodiak is seeking Staff Machine Learning Engineers, focusing on model deployment to help build the intelligence that powers the Kodiak Driver. Our ML teams work across perception, prediction, planning, and AI infrastructure to turn real-world driving data into models that enable safe and scalable autonomous trucking.

In this role, you will design and deploy machine learning systems that improve our vehicles’ ability to understand the world, predict the behavior of other road users, and make safe driving decisions. You will collaborate closely with robotics, autonomy, and infrastructure teams to continuously improve the performance of our autonomy stack using large-scale data from our growing fleet.

This is a high-impact opportunity to work on cutting-edge AI systems operating in the real world, where every mile driven improves our models and brings autonomous trucking closer to global deployment.

In this role, you will:

Help design, train, with a focus towards deploying onboard machine learning models that improve the performance/latency of the Kodiak autonomy stack which includes quantization, pruning, converting to ONNX/TensorRT, custom GPU kernels and profiling.
Help identify and achieve parity between onboard and deployed offboard models using validation on HIL
Collaborate with cross-functional teams including perception, planning, simulation, and autonomy infrastructure to integrate ML models into production systems.
Analyze real-world driving logs to identify edge cases and improve model robustness and safety.
Use profiling tooling to additionally help improve the train time for models by identifying and removing bottlenecks.
Contribute to the development of scalable AI infrastructure that supports continuous learning and deployment across Kodiak’s fleet.

What you’ll bring:

MS or PhD in Computer Science, Robotics, Machine Learning, or a related technical field, or equivalent practical experience.
6+ years experience deploying machine learning or deep learning systems in production environments.
Proficiency in Python, C++ and modern ML frameworks such as PyTorch or TensorFlow.
Experience working with large-scale distributed training systems.
Solid understanding of optimization, and machine learning fundamentals.
Strong software engineering fundamentals including testing, debugging, and system design.
Ability to work collaboratively across teams to solve complex autonomy and robotics challenges.

What we offer:

Competitive compensation package including equity and annual bonuses
Excellent Medical, Dental, and Vision plans through Kaiser Permanente, Cigna, and MetLife (including a medical plan with infertility benefits)
MetLife Legal Services, Identity & Fraud Protection, Hospital Indemnity Insurance, Accident Insurance, & Critical Illness Insurance
Flexible PTO, 10 paid holidays, 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 through Cigna, Calm through Kaiser, One Medical, Gympass, Spring Health through Cigna, Rula (mental health navigation)
Fidelity 401(k)
Commuter, FSA, Dependent Care FSA, HSA
Various incentive programs (referral bonuses, patent bonuses, etc.)

The pay range listed below reflects the base salary in our SF/Silicon Valley location, across several internal levels. Actual starting pay will be based on job-related factors including: work location, experience, relevant training, education, skill level and performance during interview. Total compensation at Kodiak includes base pay, equity, bonus and a competitive benefits package

California Pay Range

$200,000—$265,000 USD

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.

We use a third-party AI tool (Endorsed) to assist in the initial screening of applications. As part of the evaluation process, we provide Endorsed with job requirements and candidate-submitted applications. Final hiring decisions are made by our human recruitment team, and no automated system makes the ultimate decision regarding hiring. Certain features of the platform may qualify it as an Automated Employment Decision Tool (AEDT) under applicable regulations. We began using Endorsed on January 1, 2026. You can review the independent bias audit report covering our use of Endorsed [here](). By submitting your application, you acknowledge that your application may be processed by AI systems as part of the screening and selection process. If you have any questions or would like to request a separate review of your application, please contact [email protected] with "Separate Review Request" in the email subject line.

Staff Machine Learning Engineer - Deployment

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