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
Similar Jobs
What We Do
Kodiak Robotics is an autonomous technology company redefining the long-haul trucking industry.
We believe self-driving trucks will be the first economically viable application of autonomous vehicle technology. We founded Kodiak in the spring of 2018 to make that belief a reality.
Safety is our top priority. We are taking a safe and responsible approach to developing and testing our technology.
We are proud to work with some of the best in the business. We’ve built a world class team of technologists from leading autonomous driving programs who know the industry inside and out. Our combined experience and commitment to the vision will allow us to put self-driving technology on the road in the safest and most effective way.
