Staff Software Engineer, Learned & Hybrid Behavior Planning

Omaze; Mountain View (CA); On-site; USD 240,000 - 265,000; Full time

Benefits offered by this job

Competitive benefits package

Equity and bonus structure

Job summary

Kodiak Robotics, Inc. is seeking a Staff Software Engineer to enhance integration of AI models into autonomous driving behavior planning. Located in Mountain View, California, this role involves working closely with machine learning engineers to ensure safe deployment of learned components.

The ideal candidate will have expertise in behavior planning, decision-making, and robust software engineering skills, specifically in C++. The salary range for this position is $240,000 — $265,000 USD, with a comprehensive benefits package.

Qualifications

• Strong experience in autonomous vehicles or robotics.
• Deep technical background in behavior planning and decision-making.
• Ability to reason about safety and system behavior.

Responsibilities

• Lead integration of learned models into planning systems.
• Collaborate with ML teams on model improvements.
• Define validation and monitoring criteria for safety.

Skills

Experience in autonomous vehicles

Behavior planning

C++ proficiency

Python proficiency

Heuristic planning systems

Safety reasoning

Job description

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 looking for a Staff Software Engineer to help shape how learned models are integrated into behavior planning for autonomous driving. In this role, you will sit at the intersection of Planning and Machine Learning, working closely with ML engineers and autonomy teams to bring learned components into a production autonomy stack.

This is a high-impact role for someone who understands both the practical constraints of real-world planning systems and the opportunities enabled by modern learned models. You will help shape how ML improves autonomy behavior while ensuring that new capabilities are safe, measurable, debuggable, and deployable.

What You’ll Do

• Lead Planning-side integration of learned models into the behavior planning stack.
• Collaborate closely with ML teams on model improvements, requirements, evaluation, and deployment.
• Work on learned planning components as well as other ML-driven planning signals, such as behavior classification, actor intent understanding, and data-driven decision-making.
• Design integration strategies that balance learned components with existing heuristic planning systems.
• Define validation, fallback, monitoring, and safety criteria for learned planning components.
• Debug and analyze model behavior using simulation, logs, metrics, and real-world autonomy data.
• Partner with cross-functional teams across Perception, ML, Planning, Simulation, Systems, and Safety.
• Lead technical designs and mentor other engineers.

What We’re Looking For

• Strong experience in autonomous vehicles, robotics, or a related autonomy domain.
• Deep technical background in behavior planning, decision-making, or motion planning.
• Strong software engineering skills with proficiency in C++. Python proficiency is a plus.
• Experience working with heuristic or classical planning systems.
• Experience integrating or developing learned behavior policies, behavior classification, trajectory prediction, or actor intent models.
• Ability to reason about safety, system behavior, evaluation, and deployment risk.
• Excellent cross-functional communication and technical leadership skills.

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.

$240,000 — $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 https://endorsed.com/local-law-144. 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 [e-mail] with "Separate Review Request" in the email subject line.