New Grad Applied AI Engineer - Computer Vision
Description For New Grad Applied AI Engineer - Computer Vision
Kodiak Robotics, a pioneering force in autonomous vehicle technology since 2018, is seeking a New Grad Applied AI Engineer specializing in computer vision. This role presents an exciting opportunity to work at the intersection of artificial intelligence and autonomous trucking, where you'll be directly contributing to the future of transportation technology.
The position offers a competitive salary range of $135,000-$170,000, plus additional benefits including equity, bonuses, and comprehensive healthcare coverage. Based in Mountain View, CA, you'll be working in a hybrid environment with a team of experts dedicated to solving complex robotics challenges.
As an AI Engineer, you'll be responsible for designing and implementing machine learning algorithms, particularly focusing on deep neural networks for various autonomous vehicle applications. Your work will involve handling multiple sensor data types, including camera, laser, radar, and ultrasound, while developing robust solutions for lane detection, object detection, tracking, and planning.
The ideal candidate should have a strong technical background with at least a Bachelor's degree and some practical experience in deep neural networks. Proficiency in Python and C++ is essential, as is the ability to work effectively in a team environment. You'll be expected to contribute to the entire development pipeline, from dataset collection and labeling to training and validation of machine learning models.
What makes this role particularly attractive is the opportunity to work on real-world applications of AI and robotics. Kodiak's technology is already being used to deliver freight daily across Sun Belt states and in partnership with the U.S. Department of Defense. The company offers a collaborative work environment with excellent perks, including catered lunches, a dog-friendly office, and comprehensive benefits.
The role combines the excitement of cutting-edge AI research with practical implementation in autonomous vehicles. You'll be part of a team that's not just developing technology but actively shaping the future of transportation. If you're passionate about machine learning, autonomous systems, and want to work on technology that has immediate real-world impact, this position at Kodiak Robotics offers an excellent opportunity to launch your career in autonomous vehicle technology.
Responsibilities For New Grad Applied AI Engineer - Computer Vision
- Design machine learning algorithms and implement them in C++ and/or Python code
- Lead development of deep neural networks for lane detection, object detection, classification, sensor fusion, tracking, prediction, anomaly detection, and planning
- Work with camera, laser, radar, and ultrasound data and curate datasets
- Set up automated training pipelines and develop data analytics tools
- Collaborate with planning and systems engineering team
Requirements For New Grad Applied AI Engineer - Computer Vision
- BS, MS or PhD with 1+ years industry/internship experience in deep neural networks
- Skilled software engineer with Python/C++ experience
- Strong problem-solving skills
- Knowledge of data processing pipelines for training ML models in the cloud
- Team player with ownership mentality
- Ability to build and iterate quickly
- Experience with production machine learning pipelines
- Strong communication skills and documentation ability
Benefits For New Grad Applied AI Engineer - Computer Vision
- Competitive compensation package including equity and biannual bonuses
- Medical, Dental, and Vision plans through Kaiser Permanente, Anthem, and Guardian
- Flexible PTO and generous parental leave
- Dog-friendly office
- Free catered lunch
- Fully stocked kitchen
- Free EV charging
- Long Term Disability, Short Term Disability, Life Insurance
- Wellbeing Benefits (Headspace, One Medical, Gympass, Spring Health)
- 401(k)
- Commuter, FSA, Dependent Care FSA, HSA
- Various incentive programs (referral bonuses, patent bonuses)
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