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’re seeking a detail-oriented Data Quality Specialist to contribute to the advancement of autonomous truck technology. In this role, you'll be responsible for ensuring the accuracy and integrity of data collected from our autonomous trucks in both testing and production environments. Your work will directly impact the training and improvement of our autonomous driving systems by maintaining high data quality standards through thorough review and verification processes.
In this role, you will:
- Review and validate data captured from autonomous vehicles to ensure it is complete, accurate, and relevant.
- Follow structured guidelines to identify and label objects, boundaries, actions, and behaviors (e.g., vehicles, pedestrians, road signs, lane lines, and obstacles).
- Assist in data annotation and labeling efforts to support machine learning and model training.
- Conduct quality assurance audits on labeled data to verify accuracy and consistency.
- Collaborate with engineering teams to refine annotation guidelines and improve tooling.
- Contribute to the continuous improvement of the data verification workflow.
What you’ll bring:
- 2+ years of experience in data analytics and/or quality assurance.
- Familiarity with data annotation tools and related workflows.
- Excellent attention to detail and strong analytical thinking.
- Basic understanding of autonomous systems and the role of data labeling in model development.
- Experience working with sensor data from autonomous vehicles (LiDAR, radar, camera).
- Effective communication skills and strong problem-solving abilities.
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 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
Top Skills
Kodiak Robotics Mountain View, California, USA Office
1045 Terra Bella Ave, Mountain View, CA, United States, 94043
Similar Jobs
What you need to know about the San Francisco Tech Scene
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



