Senior Applied AI Engineer - Multimodal Transformers

Full Timesenior

Mountain View, CAPosted 7 days ago

Role Overview

Kodiak is hiring a Senior Applied AI Engineer - Multimodal Transformers. This is a full-time role in Mountain View. Part of Kodiak's Qa hiring, posted last week. Full responsibilities, required qualifications, and the apply link are listed in the description below.

Salary Context

Salary is not disclosed in this posting. Market median for Senior-level Qa roles is $120k-$140k (based on 26 comparable listings). Many employers share specifics during the interview process or after an initial screen.

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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 engineers to push the boundaries of how transformer architectures combine and reason over heterogeneous sensor data.This role is open to all levels – from those eager to contribute to cutting-edge research to experts driving innovation at scale.

In this role, you will:

Design and develop multimodal transformer architectures that fuse camera, LiDAR, and radar into unified representations
Research and implement cross-modal attention mechanisms, token fusion strategies, and efficient multi-stream tokenization
Build scalable training pipelines for large-scale multimodal transformers across massive real-world datasets
Explore self-supervised and contrastive pretraining objectives that learn transferable multimodal representations
Optimize transformer models for real-time inference under latency and compute constraints

What you’ll bring:

BS, MS, or PhD in AI, Computer Science, or a related field
4+ years experience with transformer architectures, particularly in multimodal or multi-stream settings
Familiarity with cross-attention, token fusion, or modality alignment techniques
Proficiency in Python and deep learning frameworks like PyTorch or TensorFlow
Strong understanding of scalable training for large models, including distributed training and mixed-precision optimization
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

$200,000—$260,000 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](https://endorsed.com/local-law-144). 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.

About Kodiak

Kodiak

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Frequently Asked Questions

How do I apply for the Senior Applied AI Engineer - Multimodal Transformers position at Kodiak?

Use the Apply button above to submit your application directly to Kodiak. Most applications take less than 5 minutes if your resume and contact details are ready, and you'll be routed to the employer's official application system to finish.

Where is the Senior Applied AI Engineer - Multimodal Transformers position at Kodiak located?

This position is based in Mountain View. Kodiak has not indicated remote or hybrid options for this role, so candidates should plan for on-site work.

What does a Senior Applied AI Engineer - Multimodal Transformers at Kodiak earn?

Kodiak has not disclosed a salary range in this posting. Many employers share specifics later in the interview process; you can also ask during a recruiter screen if compensation transparency is important to you.

When was the Senior Applied AI Engineer - Multimodal Transformers role at Kodiak posted?

This role was posted on July 2, 2026 (7 days ago). It's still listed as actively hiring; we re-confirm openings against the source system multiple times per day and remove closed roles.

How much experience does the Senior Applied AI Engineer - Multimodal Transformers role at Kodiak require?

This is a senior-level position. Most senior roles call for 5+ years of directly relevant experience. Kodiak lists their specific requirements in the description below, so review the must-have qualifications closely before applying.

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