Applied AI Engineer, Kodiak Robotics

• BS, MS, or PhD in AI, Computer Science, or a related field, or at least 2-3 years of industry experience
• Experience with diffusion models, autoregressive learning, or generative AI methods
• Proficiency in Python and deep learning frameworks like PyTorch or TensorFlow
• Strong understanding of uncertainty modeling and self-supervised learning
• Passion for building AI that continuously adapts and learns

• We are looking for engineers to develop AI that anticipates uncertainty, enhances decision-making, and refines its own understanding of the world
• This role is open to all levels—from those eager to contribute to cutting-edge research to experts driving innovation at scale
• Develop generative models that enhance adaptability and improve AI robustness
• Research and implement diffusion-based, autoregressive, and variational techniques for real-world AI applications
• Apply generative methods to anticipate challenges and reinforce decision-making
• Build self-improving AI pipelines that continuously refine model understanding
• Optimize models for efficient, scalable, and interpretable AI decision-making

• Remote-friendly work environment
• 401k
• Generous PTO policy
• Life insurance
• Assortment of medical (PPO/HMO/HDHP), dental, vision, and FSA plans
• Family-friendly company events
• Dog-friendly office
• Employee-driven fitness classes
• Beautiful, renovated facilities in Mountain View, CA and Lancaster, TX
• Free EV charging
• Trivia and board game nights

Total funding: $240m

Global supply chains rely on frictionless long-haul trucking freight networks, but the repetitive and stationary nature of the job has resulted in a lack of willing drivers. Whilst this has been partially resolved through the introduction of self-driving trucks, such systems are notoriously difficult to maintain which ultimately leads to significant downtime.