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Applied Scientist Machine Learning Jobs in California

Adobe

Applied Scientist

San Jose, CA · On-site

They are seeking an Applied Scientist to conduct research and development in training large-scale ... D. degree in Computer Science, Machine Learning, or a related field. • Extensive practical ...

Amazon

Sr Applied Scientist

Sunnyvale, CA · On-site

$107K - $146K/yr

As an Applied Scientist, you will work with talented peers pushing the frontier of computer vision and machine learning technology to deliver the best experience for our neighbors. This is a great ...

Amazon

Sr Applied Scientist

Sunnyvale, CA · On-site

$107K - $146K/yr

As an Applied Scientist, you will work with talented peers pushing the frontier of computer vision and machine learning technology to deliver the best experience for our neighbors. This is a great ...

Microsoft

Senior Applied Scientist

Mountain View, CA · On-site

In this role, the Senior Applied Scientist will design and implement state-of-the-art machine learning models and algorithms that power key systems within Microsoft Ads, Microsoft Audience Network ...

Amazon

Sr Applied Scientist, Ring AI

Sunnyvale, CA · On-site

$107K - $146K/yr

As an Applied Scientist, you will work with talented peers pushing the frontier of computer vision and machine learning technology to deliver the best experience for our neighbors. This is a great ...

Amazon

Sr Applied Scientist, Ring AI

Sunnyvale, CA · On-site

$107K - $146K/yr

As an Applied Scientist, you will work with talented peers pushing the frontier of computer vision and machine learning technology to deliver the best experience for our neighbors. This is a great ...

Adobe, Inc.

Staff Applied Scientist

San Jose, CA · On-site

Adobe's Applied Science & Machine Learning (ASML) organization is looking for applied research scientists to help us build the next generation of multimodal foundation models. We are seeking ...

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All JobsApplied Scientist Machine Learning JobsApplied Scientist Machine Learning Jobs in California

Applied Scientist Machine Learning information

See California salary details

$22K

$127K

$199.8K

How much do applied scientist machine learning jobs pay per year?

As of Aug 10, 2026, the average yearly pay for applied scientist machine learning in California is $127,000.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,391.00 and $154,718.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an applied scientist in machine learning, and why are they important?

To thrive as an Applied Scientist in Machine Learning, you need a solid background in mathematics, statistics, computer science, and typically a master's or PhD in a related field. Proficiency in programming languages like Python or Java, experience with ML frameworks such as TensorFlow or PyTorch, and familiarity with cloud platforms and data processing tools are crucial. Strong problem-solving skills, intellectual curiosity, and the ability to communicate complex ideas clearly make candidates stand out. These skills ensure effective development, implementation, and communication of advanced machine learning solutions that drive business impact.

How does an applied scientist in machine learning typically collaborate with software engineers and data engineers on projects?

Applied Scientists in Machine Learning often work closely with software engineers and data engineers to bring machine learning models from prototype to production. They usually develop and validate models, while data engineers assist in preparing and managing large datasets, and software engineers help integrate models into scalable applications. Effective communication and cross-functional teamwork are essential, as the role requires translating scientific findings into practical solutions that align with business goals. Regular meetings, code reviews, and collaborative problem-solving sessions are common, ensuring smooth transitions between research and deployment phases.

What does an applied scientist in machine learning do?

An Applied Scientist in Machine Learning develops and implements machine learning models to solve real-world problems. They work on collecting and preprocessing data, designing algorithms, and evaluating model performance. Their work often bridges research and product development, collaborating with engineers and data scientists to deploy solutions in production. Applied Scientists also keep up-to-date with the latest advancements in machine learning to continuously improve systems and outcomes.
What are the most commonly searched types of Applied Scientist Machine Learning jobs in California? The most popular types of Applied Scientist Machine Learning jobs in California are:
What are popular job titles related to Applied Scientist Machine Learning jobs in California? For Applied Scientist Machine Learning jobs in California, the most frequently searched job titles are:
What job categories do people searching Applied Scientist Machine Learning jobs in California look for? The top searched job categories for Applied Scientist Machine Learning jobs in California are:
Applied Scientist Machine Learning jobs near you
Infographic showing various Applied Scientist Machine Learning job openings in California as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $127,000 per year, or $61.1 per hour.

Machine Learning Engineer / Applied Scientist, Prediction & Planning

Waymo

San Francisco, CA • On-site

$175K - $215K/yr

Other

Re-posted 3 days ago

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.

The Predictive Planning team (PrePlan) develops and deploys state-of-the-art machine learning solutions that predict the future state of the world and plan the Waymo Driver's behavior. Our mission is to transform Waymo's unprecedented scale of driving data into robust, generalizable, and performant deep neural networks. These models enable the autonomous vehicle to navigate complex environments safely and efficiently.

You will:

  • Design, implement, and evaluate state-of-the-art generative models for autonomous vehicle planning and prediction
  • Develop next-generation, ML-powered systems that enhance the capabilities of the ML driver and accelerate the rapid scaling of Waymo's business
  • Translate open-ended, real-world driving challenges into well-defined machine learning problems, applying cutting-edge techniques, including foundation models and reinforcement learning
  • Write high-quality, scalable, and thoroughly tested code to bring cutting-edge research into production
  • Partner with world-class researchers, engineers, and product managers to deliver safe and smooth planning behaviors, and publish findings at top-tier academic venues

You have:

  • PhD in Computer Science, Machine Learning, Robotics, a related technical field, or equivalent practical experience
  • A proven track record of publications in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, ICRA, IROS, RSS, CoRL, ACL, or EMNLP)
  • Demonstrated impact on the broader ML community through influential research, widely adopted open-source projects, or significant industry contributions
  • Hands-on expertise with modern deep learning frameworks, for example JAX or PyTorch
  • Proficient programming skills in Python and/or C++, coupled with strong analytical and debugging abilities

We prefer:

  • Specialized research experience in deep learning, reinforcement learning, causal reasoning, or foundation models
  • Prior industry experience (e.g. internships) in applied ML research or software development
  • Domain expertise in solving motion planning, prediction, or related robotics problems
  • Hands-on experience deploying, evaluating, and maintaining ML-based systems in real-world, production environments

#LI-Hybrid

The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.

Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.

Salary Range
$175,000—$215,000 USD

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