2027 Summer Intern, MS/PhD, Software Engineer, Sys Intel & Machine Learning
Immigration summary
Visa sponsorship
This employer sponsors this kind of work repeatedly, and is still filing this year.
241 recent H-1B filings · 147 similar-role filings
View visa evidenceGreen card sponsorship
This employer has recently sponsored green cards at scale.
47 recent certified PERM filings · 38 similar-role filings
View green card evidenceJob description
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.
Software Engineering builds the brains of Waymo's fully autonomous driving technology. Our software allows the Waymo Driver to perceive the world around it, make the right decision for every situation, and deliver people safely to their destinations. We think deeply and solve complex technical challenges in areas like robotics, perception, decision-making and deep learning, while collaborating with hardware and systems engineers. If you’re a software engineer or researcher who’s curious and passionate about Level 4 autonomous driving, we'd like to meet you.
The subteam for this role will be:
The Model Optimization & ML Runtime team (within Smart Perception / Machine Learning) is responsible for maximizing the capability, efficiency, and hardware performance of Waymo's cutting-edge perception and foundation models. We bridge the gap between large-scale multi-task ML research (Vision Transformer backbones, 30+ perception heads, multi-sensor fusion) and real-time onboard vehicle deployment across custom automotive accelerators, developing core optimization frameworks (parameter-efficient fine-tuning, quantization, compilation, and quantization-aware training) that power the autonomous Waymo Driver.
Waymo interns partner with leaders in the industry on projects that create impact to the company. We believe learning is a two-way street: applying your knowledge while providing you with opportunities to expand your skill-set. Interns are an important part of our culture and our recruiting pipeline. Join us at Waymo for a fun and rewarding internship!
You will:
- Design, implement, and benchmark parameter-efficient fine-tuning (LoRA / QLoRA) modules in JAX/Flax for multi-task Vision Transformer backbones
- Develop dual-level distillation pipelines (intermediate feature matching and task-head logit distillation) to mitigate multi-task regressions during large-scale data scaling
- Collaborate with model optimization, quantization, and latency teams to validate static weight folding and low-precision quantization, ensuring zero latency overhead on onboard compute platforms
- Conduct extensive empirical ablations and evaluate perception metrics on large-scale autonomous driving datasets across diverse geographic domains
You have:
- Currently pursuing a PhD or Master's in Computer Science, Electrical Engineering, Machine Learning, Robotics, or a related technical field
- Strong software engineering and deep learning development skills in Python and modern frameworks (JAX, Flax, PyTorch, or TensorFlow)
- Solid theoretical understanding and hands-on experience with deep learning foundation models, Transformer architectures, and multi-task learning
- Experience with model compression, parameter-efficient fine-tuning (e.g., LoRA, QLoRA, adapters), or quantization and knowledge distillation techniques
We prefer:
- Publication record at top-tier computer vision or machine learning conferences (e.g., CVPR, ICCV, ECCV, NeurIPS, ICLR)
- Hands-on experience with model quantization (PTQ, QAT, INT8/INT4/MX4), low-precision numerics, or hardware-aware model optimization
- Experience training and scaling large vision backbones or multi-modal models on distributed accelerator clusters (TPUs / GPUs)
- Familiarity with autonomous driving perception tasks (3D object detection, semantics, tracking, or pedestrian intent prediction)
General Perks
- Help solve challenging problems with a direct impact on the company
- Competitive compensation packages with a housing/relocation bonus (if applicable)
- Medical, dental, and vision insurance
- Fun intern events and networking opportunities
Onsite Perks
- Free breakfast, lunch, dinner, and snacks
- Free access to Google shuttles
- Onsite gym
Note: This will be a hybrid onsite internship position. We will accept resumes on a rolling basis until the role is filled. To be in consideration for multiple roles, you will need to apply to each one individually - please apply to the top 3 roles you are interested in.
The expected hourly rate for this full-time position is listed below. Interns are also eligible to participate in the Company’s generous benefits programs, subject to eligibility requirements.Hourly Masters Pay$70—$70 USDThe expected hourly rate for this full-time position is listed below. Interns are also eligible to participate in the Company’s generous benefits programs, subject to eligibility requirements.Hourly PhD Pay$85—$85 USD
Sponsorship evidence
Why Openbound reached the conclusions above.
Visa sponsorship evidence
Current posting
Silent on sponsorship
Employer H-1B history
- 241
- recent certified H-1B filings
- 176
- new-hire petitions
- 147
- filings for similar roles
- 277
- so far in FY2026
Filed titles like this role: software engineer · software engineer machine learning
More evidence details
- 147 certified H-1B filings for this same role, 176 new-hire petitions across the employer, and 237 new hires already this year
- 147 certified H-1B filings for this same role
- 241 recent certified H-1B filings across the employer
- Still filing this year — 277 filings in FY2026
- 108 USCIS H-1B new-employment approvals, counted separately from LCA filings
- Strong filing activity in CA
- 351 further USCIS approvals for extensions or transfers
- The posting says nothing about sponsorship either way
Strong filing activity in CA.
Green card sponsorship evidence
Employer PERM history
- 47
- recent certified PERM filings
- 38
- filings for similar roles
- 46
- filings in this location
Filing history reflects past employer behavior; it isn't a promise for this opening.
All open roles at WaymoHow Openbound evaluates sponsorship
Visa history uses official U.S. Department of Labor H-1B LCA disclosure data and USCIS H-1B petition history. Green card history uses DOL PERM disclosure data. Each is read for the employer as a whole, for roles like this one, and for this location, weighted toward the most recent fiscal years.
An employer is matched to its filing entities by verified legal name and reviewed aliases; a match is never made on a name resemblance alone. Where no verified entity can be matched, the page says so and draws no conclusion from the absence. 115 filing titles were examined for this employer.
What this posting states outranks history in both directions, and an employer's published policy outranks past filings. Filing history reflects past behavior; it is not a promise of sponsorship for this opening, and none of this is legal advice.