Senior Software Engineer, Kodiak Robotics
Planning ML Integration
$160-235k
+ Equity + Annual bonuses
More information about location
Self-driving technology for long-haul trucks
Be an early applicant
Self-driving technology for long-haul trucks
201-500 employees
Be an early applicant
$160-235k
+ Equity + Annual bonuses
More information about location
201-500 employees
Company mission
Kodiak Robotics' mission is to carry freight forward—so people, partners, and the planet thrive.
Role
Who you are
- Strong software engineering skills with proficiency in C++. Python proficiency is a plus
- Experience integrating ML models or learned components into a real-time system
- A strong background in robotics, planning, optimization, and mathematics (MS, PhD, or equivalent experience)
- Industry experience in robotics or autonomous driving
- Experience working in large-scale or safety-critical systems with strict performance requirements
- Experience evaluating or interpreting ML model outputs
- Strong analytical skills, including the ability to reason about algorithmic trade-offs and system behavior
- Excellent communication skills and comfort working across teams
- A desire to collaborate with other teams outside of planning
What the job involves
- We're building the next generation of planning capabilities by integrating learned models into autonomous vehicle decision-making
- You'll translate neural network outputs to reliable vehicle behaviors
- In this role, you will enhance our motion planner by incorporating machine learning models
- You will define the interfaces, requirements, and integration strategies necessary to meaningfully improve decision-making in complex, real-world environments
- In addition to this effort, you will contribute broadly to the evolution of our planning stack by developing new features, improving core algorithms, and strengthening the overall architecture
- This is a high-impact role for an engineer who enjoys bridging disciplines, shaping emerging capabilities, and advancing state-of-the-art autonomy through thoughtful, rigorous engineering
- Incorporate neural networks into the planning stack, working closely with ML, perception, and systems teams
- Evaluate how learned inputs influence planner performance, in simulation and on-road
- Architect fallback, hybrid, or arbitration strategies that maintain safety and reliability when learned models are uncertain or degraded
- Contribute to the broader planning system by designing and implementing new planning behaviors, search strategies, optimizations, and structural improvements
- Write high-quality C++ code that meets real-time constraints and supports safety-critical deployment
- Participate in code reviews, design discussions, and cross-team planning to ensure alignment and technical excellence
Our take
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.
Kodiak Robotics develops self-driving technology for long-haul trucks, providing wing mirrors built with sensors called Kodiak SensorPods. These sensors provide the technology necessary for the trucks to be driven safely and autonomously and have been designed to be replaced or serviced rapidly to minimize downtime.
Whilst the company’s most significant challenge will present itself as other self-driving truck providers, Kodiak Robotics has taken a unique approach by recognizing the high-maintenance nature of existing self-driving systems, innovating upon this through its easily replaceable SensorPods. Through this approach and several successful rounds of funding, the company aims to fill empty truck driving positions with safer AI drivers, whilst ensuring its technology is quick and simple to maintain.
Steph
Company Specialist at Welcome to the Jungle
Insights
21% employee growth in 12 months
Company
Funding (last 2 of 3 rounds)
Sep 2023
$75m
CONVERTIBLE
Nov 2021
$125m
SERIES B
Total funding: $240m
Company benefits
- 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
Company HQ
Mountain View, CA
Leadership
Don Burnette
(CEO)Experience as Co-founder of Otto. Software Technical Lead at Uber from 2016 to 2018.
Salary benchmarks
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