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60 Waymo Machine Learning Scientist Jobs Hiring Near You

Waymo

Machine Learning Engineer - Mapping

Mountain View, CA · On-site

$204K - $259K/yr

Waymo is an autonomous driving technology company with the mission to be the world's most trusted ... B.S. in Computer Science, a similar technical field, or equivalent practical experience. It's a ...

Waymo

Machine Learning Engineer - Mapping

Mountain View, CA · On-site +1

$204K - $259K/yr

Waymo is an autonomous driving technology company with the mission to be the world's most trusted ... B.S. in Computer Science, a similar technical field, or equivalent practical experience. It's a ...

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Waymo Jobs Information

What is a Machine Learning Scientist job?

A Machine Learning Scientist researches, develops, and applies machine learning models to solve complex problems. They work on designing algorithms, improving model performance, and analyzing large datasets to extract valuable insights. Their role often involves experimenting with new techniques, optimizing existing models, and collaborating with engineers and data scientists to deploy solutions. Machine Learning Scientists typically have expertise in statistics, mathematics, and programming languages like Python. They work in industries such as healthcare, finance, and technology to drive innovation using artificial intelligence.

What are the key skills and qualifications needed to thrive in the Machine Learning Scientist position, and why are they important?

To thrive as a Machine Learning Scientist, you need strong skills in mathematics, statistics, programming (typically in Python or R), and a graduate degree in computer science, data science, or a related field. Expertise in machine learning frameworks (such as TensorFlow, PyTorch, or scikit-learn), proficiency with data processing tools, and experience with cloud platforms (like AWS or GCP) are commonly required; certifications in these can be advantageous. Critical thinking, problem-solving, and effective communication are important soft skills for collaborating with cross-functional teams and conveying complex concepts. These abilities enable Machine Learning Scientists to build effective models, deliver actionable insights, and drive innovation within organizations.

What are the typical daily tasks and collaboration opportunities for a Machine Learning Scientist?

A typical day for a Machine Learning Scientist involves collecting and analyzing large datasets, designing and training machine learning models, and evaluating model performance to ensure accuracy and reliability. You'll often collaborate with data engineers, software developers, and domain experts to define project goals, prepare data, and integrate solutions into production systems. Regular team meetings, code reviews, and brainstorming sessions are common, fostering an environment of shared learning and problem-solving. This collaborative structure not only enhances project outcomes but also offers valuable opportunities for continuous professional growth and skill development.

What is it like to work at Waymo?

Waymo is a technology company that values innovation, collaboration, and safety, fostering an environment where employees can work together to develop and implement autonomous driving solutions.

The company's structure is organized into various teams, including software engineering, hardware development, and operations, allowing employees to specialize in their areas of expertise and contribute to the development of self-driving cars. Waymo's work environment is designed to encourage creativity and experimentation, with access to cutting-edge technology and resources.

Working at Waymo may appeal to individuals who are passionate about transforming the transportation industry and have a strong interest in artificial intelligence, machine learning, and software development, as the company offers opportunities to work on complex technical challenges and make a meaningful impact on society.
What are the most popular jobs at Waymo?
What are the most popular categories at Waymo?
Infographic showing various Machine Learning Scientist job openings at Waymo in the United States as of May 2026, with employment types broken down into 100% Full Time. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution.
Principal Software Engineer, ML Flywheel Technical Lead

Principal Software Engineer, ML Flywheel Technical Lead

Waymo

San Diego, CA

Other

Posted 4 days ago

Job description

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. 

Every mile driven by a Waymo car is a unique and valuable piece of data that can be leveraged into improving our machine learning models, and ultimately the safety and capabilities of the Waymo Driver. Charting the path from collection of a piece of data, to curation, (auto-)labeling, model training and evaluation, all the way to model deployment and monitoring is a process of continuous scaling and quality improvement of the entire ML lifecycle. The Area Technical Lead for the Waymo machine learning flywheel is responsible for architecting, connecting, automating and improving the entire span of this self-improvement process in close collaboration with Waymo's infrastructure, modeling and evaluation teams. They are directly accountable to Waymo's leadership for the organization's ML data strategy and its impact on Driver quality.

You will report directly to our Distinguished Engineer, Foundation Models.

You Will:

  • Architect a path towards every autonomous mile driven by a Waymo car to be automatically incorporated into an automated data-driven self-improvement loop for the Waymo Driver.
  • Enable a data flywheel to serve the demands of scalable pre-training, post-training targeted to relevant critical behaviors, as well as Driver simulation and validation.
  • Enable a modeling flywheel to efficiently consume that data to reliably generate updated models that are validated and deployable with minimal human toil.
  • Coordinate cross-functional efforts in partnership with data and ML infrastructure teams, resource planning, logging infrastructure, modeling and validation teams to accelerate the velocity, impact and leverage of driving data on the Waymo Driver.
  • Act as the steward of data quality, by providing tooling and metrics to evaluate the impact of mining, selection and curation on the modeling pipeline performance.
  • Articulate the strategy for incorporating diverse data sources, including third-party and synthetic data into that improvement flywheel.
  • Drive innovation across all axes of performance and efficiency, from Driver quality, to scalability, cost, engineering velocity, model architecture and performance.

You Have:

  • Master's degree or PhD in Computer Science, Engineering, or a related technical field
  • 10+ years of experience in ML model development, and you have 2+ years experience with large-scale vision, video, or multi-modal foundation model development and their integration in end-to-end models
  • 6+ years of experience in ML-driven production systems that develops models with large-scale data, training, evaluation, and deployment
  • 6+ years of experience in a technical leadership role leading technical teams and setting technical directions in large ML Engineering organizations
  • Demonstrated expertise in large-scale machine learning and its key components: pre-training, post-training, and validation. Deep understanding of both infrastructure and quality aspects.
  • Track record of architecting and standing up a machine learning flywheel at scale for mission critical applications.
  • Experience with driving model quality improvements through systematic data scaling and curation.
  • Communication and interpersonal skills. Ability to inspire, influence and coordinate across functions and disciplines.

We Prefer:

  • PhD in computer science.
  • Experience in multi-modal LLM model development, and their infrastructure.
  • Familiarity with multi-task, end-to-end models and their development challenges.

Apply