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Listed location: Mountain View, California, USA
Work arrangement: onsite. A remote label does not confirm worldwide eligibility or visa sponsorship.
Read the employer’s description for qualifications, compensation and work eligibility. Confirm the position is still open on the application page.
Job description supplied by Waymo; category and skill labels may be inferred. How our listings work · Report a problem
Job 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.
Machine Learning models are at the core of Waymo's fully autonomous driving technology. Our models allow 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 perception, planning and control while collaborating with hardware and systems engineers. If you're curious and passionate about Level 4 autonomous driving, we'd like to meet you.
Waymo interns work with leaders in the industry on projects that deliver significant impact to the company. We believe learning is a two-way street: applying your knowledge while providing you with opportunities to expand your skillset. Interns are an important part of our culture and our recruiting pipeline. Join us at Waymo for a fun and rewarding internship!
This internship will be based on-site at our headquarters in Mountain View, CA.
You will:
- Design and implement state-of-the-art multi-modality (camera/radar/lidar/audio) and multi-task perception models. Potential project areas include:
- 3D object detection and tracking
- Open vocabulary detection applying world knowledge models
- 3D occupancy detection
- Semantic segmentation
- Large-scale foundation models
- Pre-training and self-supervised learning through forecasting
- Train and evaluate ML models on our vast and high fidelity data from Waymo driving logs
- Gain experience using large scale ML infrastructure and working in a team environment
You have:
- Enrolled in a Masters or PhD program in Computer Science, Robotics, or a similar technical field of study or enrolled in a master's program with a strong publication record
- Experience in Python
- Experience building ML models with JAX, PyTorch or Tensorflow
We prefer:
- Strong track record of high quality ML / CV research. Publications at top-tier conferences like CVPR, ICCV, ECCV, ICLR, ICML, ICRA, IROS, RSS, NeurIPS, AAAI, IJCV, PAMI
- Experience in object detection, segmentation, multiple-object tracking audio perception or occupancy detection
Skills mentioned
Categories
Frequently asked questions
Is the 2027 Summer Intern, MS/PhD, Semantics position at Waymo remote?
The 2027 Summer Intern, MS/PhD, Semantics role at Waymo does not have a confirmed remote arrangement in our data. Check the employer description for its work location.
What type of employment is the 2027 Summer Intern, MS/PhD, Semantics role?
Waymo is hiring for a full-time 2027 Summer Intern, MS/PhD, Semantics position.
Which skills are mentioned for the 2027 Summer Intern, MS/PhD, Semantics job at Waymo?
Detected skill labels include Python, PyTorch, TensorFlow, JAX. Check the employer description to distinguish required skills from preferred experience.
How do I apply for the 2027 Summer Intern, MS/PhD, Semantics position at Waymo?
You can apply for the 2027 Summer Intern, MS/PhD, Semantics role directly through Waymo's official application link provided on this page.
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