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 Machine Learning Engineers focussing on data, pipelines and tooling 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 develop the data pipeline which helps design 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:- Work with ML team to automate existing and new pipelines using AirFlow/Metaflow like orchestration frameworks.
- Utilize different auto generated / manually labeled signals to stratify datasets to dedup data and improve the information content of ML dataset.
- Improve and support the metrics dashboard and the underlying datastore to allow it to be scalable for growing volume of tests, performant and cost effective.
- Be the advocate for additional tooling to simplify and improve current processes to become more powerful and automated . This includes but is not limited to dataset curation and mining, evaluation and problem discovery, labelling and triage including utilizing LLM’s and offboard models.
- Contribute to the development of scalable AI infrastructure that supports continuous learning and deployment across Kodiak’s fleet.
- MS or PhD in Computer Science, Robotics, Engineering, Mathematics, or a related technical field, and 3+ years of practical experience working with ML teams.
- Proficiency in Python
- Proven ability to build scalable ELT pipelines and data models using SQL and modern data lakes using automated workflow orchestration tools such as Apache Airflow / MetaFlow
- 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
