Technical Lead, Multimodal Transformers

Kodiak; Mountain View (CA); On-site; USD 230,000 - 300,000; Full time

Benefits offered by this job

Competitive compensation including equ

Annual bonuses

Excellent medical, dental, vision

Dog-friendly office

Free catered lunch

EV charging

Job summary

Kodiak Robotics, Inc. is seeking a senior technical leader to own the architecture roadmap for multimodal transformers fusing camera, LiDAR, and radar. You will lead end-to-end projects from framing to production and set architectural direction for scalable training pipelines.

With a PhD or MS/BS and 8+ years of experience, you will mentor engineers, drive cross-modal research, and ensure AI systems meet safety and latency requirements in real-world trucking applications.

Qualifications

• PhD with 5+ years of industry experience or MS/BS with 8+ years in AI/CS.
• Track record of leading multi-engineer technical efforts from research through production.
• Deep expertise in transformer architectures, particularly multimodal or multi-stream settings.
• Strong command of cross-attention, token fusion, and modality alignment techniques.
• Experience mentoring engineers and growing technical talent.
• 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.

Responsibilities

• 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; decide 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 for transferable multimodal representations.
• Partner with perception, planning, and infrastructure leads to align model design with system-level latency and compute budgets.

Skills

Transformer architectures

Multimodal AI

Python

PyTorch

Distributed training

Mentoring

Cross-attention

Token fusion

Leadership

Education

PhD

MS/BS + experience

Tools

PyTorch

Job description

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.

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
• 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

The pay range listed below reflects the base salaryin 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

$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.