The Role
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 highly skilled New Grad Software Engineer with a focus on deep learning for computer vision applications to join us and solve real-world robotics problems.
In this role, you will:
- Be responsible for designing machine learning algorithms and implementing them in robust, efficient, and well-tested C++ and/or Python code.
- Lead the development of deep neural networks to solve real-world robotics challenges such as lane detection, object detection and classification, sensor fusion, tracking, prediction, anomaly detection, and planning.
- Work with camera, laser, radar, and ultrasound data and curate datasets for machine learning.
- Set up automated training pipelines and develop data analytics tools to incrementally improve our performance on a growing dataset.
- Collaborate closely with other experts on the team, including the planning and systems engineering team.
Qualifications:
- Strong technical background. BS, MS or PhD with academic or at least 1+ years industry/internship experience in designing and implementing deep neural networks. You are a skilled software engineer with experience in Python/ C++ and strong problem-solving skills. You are passionate about solving real-world robotics problems, and you have ideally worked on autonomous robots before. You ideally also have a strong knowledge of data processing pipelines for training ML models in the cloud.
- A team player. You take ownership and work with the team to deliver exceptional results. You are interested in the performance of the entire system across engineering disciplines.
- Ability to build and iterate quickly. You enjoy working fast and smart, and you are comfortable in the earlier stages of developing an algorithm from scratch.
- Hands on. You are not only passionate about ML research but also experienced working with production machine learning pipelines, from dataset collection and labeling to training and validation.
- Great communicator. You have experience writing clear, concise, and detailed documentation. You can enable your colleagues to leverage the ML models resulting from your work in their algorithms and systems.
Benefits:
- 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 annual salary range for this full-time position is $135,000-$170,000 + bonus + equity + benefits. Actual salary ranges will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Please note that the compensation details listed above are base salary only and do not include bonus, equity, or benefits.
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.
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The Company
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.
