Job description

Kodiak AI, Inc. (Nasdaq: KDK), founded in 2018, is a leader in Physical AI, developing driverless technology that powers machines that move. Its Kodiak Driver is a vehicle-agnostic autonomous driving system that combines AI-powered software with modular hardware. Today it operates in long-haul trucking, industrial trucking, and defense. In 2024, Kodiak launched commercial Driver-as-a-Service operations with no one in the cab, and plans to launch driverless long-haul service between Dallas and Houston by the end of 2026. Kodiak has partnered with many of the biggest names in freight, including Bosch for scaled hardware production, AWS, and leading customers including Atlas Energy Solutions, IKEA, Bridgestone, Werner Enterprises, C.R. England, Roehl Transport, and General Dynamics Land Systems. Kodiak's autonomy stack is built on AI that fuses diverse sensor streams into a unified, actionable understanding of the world. We are developing GigaFusionNet, a large-scale multimodal transformer that learns rich, joint representations across camera, LiDAR, and radar through attention-based fusion. We are looking for a technical leader to own the architecture direction of this effort and grow the engineers building it. This is a senior individual contributor role with significant scope. You will set technical direction for multimodal fusion at Kodiak, lead the workstream executing against it, and be accountable for the results landing on trucks. In this role, you will: Own the architecture roadmap for multimodal transformers that fuse camera, LiDAR, and radar into unified representations Lead the project end to end: problem framing, experiment design, implementation, and production deployment Drive research direction on cross-modal attention, token fusion strategies, and efficient multi-stream tokenization, and make the calls on what gets built Set the technical bar through design reviews, code reviews, and architectural decisions on scalable training pipelines Mentor junior and mid-level engineers, and raise the level of research execution across the org Define the pretraining strategy, including self-supervised and contrastive objectives that learn transferable multimodal representations Partner with perception, planning, and infrastructure leads to align model design with system-level latency and compute budgets What you’ll bring: PhD with 5+ years of industry experience, or MS/BS with 8+ years, in AI, Computer Science, or a related field Track record of leading multi-engineer technical efforts from research through production Deep expertise in transformer architectures, particularly in multimodal or multi-stream settings Strong command of cross-attention, token fusion, and modality alignment techniques Experience mentoring engineers and growing technical talent Expert proficiency in Python and PyTorch, including large-scale distributed training and mixed-precision optimization Ability to influence technical direction across teams without formal authority Passion for building AI that reasons over the full breadth of sensory input to operate safely in the real world What we offer: Competitive compensation package including equity and annual bonuses Excellent Medical, Dental, and Vision plans through Kaiser Permanente, Cigna, and MetLife (including a medical plan with infertility benefits) MetLife Legal Services, Identity & Fraud Protection, Hospital Indemnity Insurance, Accident Insurance, & Critical Illness Insurance Flexible PTO, 10 paid holidays, 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 through Cigna, Calm through Kaiser, One Medical, Gympass, Spring Health through Cigna, Rula (mental health navigation) 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 California Pay Range $230,000 — $300,000 USD 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. We use a third-party AI tool (Endorsed) to assist in the initial screening of applications. As part of the evaluation process, we provide Endorsed with job requirements and candidate-submitted applications. Final hiring decisions are made by our human recruitment team, and no automated system makes the ultimate decision regarding hiring. Certain features of the platform may qualify it as an Automated Employment Decision Tool (AEDT) under applicable regulations. We began using Endorsed on January 1, 2026. You can review the independent bias audit report covering our use of Endorsed [here]( endorsed.com ). By submitting your application, you acknowledge that your application may be processed by AI systems as part of the screening and selection process. If you have any questions or would like to request a separate review of your application, please contact careers@kodiak.ai with "Separate Review Request" in the email subject line.

Requirements

Must-haves

Own the architecture roadmap for multimodal transformers that fuse camera, LiDAR, and radar into unified representations
Lead the project end to end: problem framing, experiment design, implementation, and production deployment
Drive research direction on cross-modal attention, token fusion strategies, and efficient multi-stream tokenization, and make the calls on what gets built
Set the technical bar through design reviews, code reviews, and architectural decisions on scalable training pipelines
Mentor junior and mid-level engineers, and raise the level of research execution across the org
Define the pretraining strategy, including self-supervised and contrastive objectives that learn transferable multimodal representations
Partner with perception, planning, and infrastructure leads to align model design with system-level latency and compute budgets
PhD with 5+ years of industry experience, or MS/BS with 8+ years, in AI, Computer Science, or a related field
Track record of leading multi-engineer technical efforts from research through production
Deep expertise in transformer architectures, particularly in multimodal or multi-stream settings
Strong command of cross-attention, token fusion, and modality alignment techniques
Experience mentoring engineers and growing technical talent
Expert proficiency in Python and PyTorch, including large-scale distributed training and mixed-precision optimization
Ability to influence technical direction across teams without formal authority
Passion for building AI that reasons over the full breadth of sensory input to operate safely in the real world

Nice-to-haves

None flagged.

Application prep

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Keywords to mirror

aiawspython

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Pto

Parental Leave