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Deep Learning Scientist Jobs in California (NOW HIRING)

Currently pursuing a Masters or PhD program in Computer Science, Machine Learning, Robotics, or similar field * Strong background in deep learning, with experience in model design, training and ...

Currently pursuing a Masters or PhD program in Computer Science, Machine Learning, Robotics, or similar field * Strong background in deep learning, with experience in model design, training and ...

Requirements Candidates for the Deep Learning Algorithm Developer position should have a strong background in engineering, computer science, physics, and/or mathematics. Experience with PyTorch ...

Learning Scientist

Mountain View, CA · On-site

$140 - $200/hr

Deep grounding in learning science -- the experimental literature on how people acquire and retain skills (retrieval, spacing, feedback, transfer, expertise development) and where its limits are

D. in computer science, electrical engineering or related discipline * Demonstrated hands-on experience designing, training and deploying deep learning models * Ability to deliver high quality, well ...

Our team is made up of mathematicians, physicists, and computer scientists who are deeply ... Strong background in machine learning, deep learning, or related fields. * 2+ years of experience ...

Showing results 41-60

Deep Learning Scientist information

See California salary details

$37K

$121.1K

$193.9K

How much do deep learning scientist jobs pay per year?

As of Sep 3, 2026, the average yearly pay for deep learning scientist in California is $121,131.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,200.00 and $134,200.00 per year, depending on experience, location, and employer.

What is a deep learning scientist?

Deep Learning Scientists are experts who design, develop, and implement advanced machine learning models inspired by the structure and function of the brain, known as artificial neural networks. They work with large datasets to train algorithms that can recognize patterns, make predictions, and solve complex problems in areas such as image recognition, natural language processing, and autonomous systems. Deep Learning Scientists often collaborate with software engineers, data scientists, and domain specialists to deploy models in real-world applications like healthcare, finance, and self-driving cars.

What are the key skills and qualifications needed to thrive as a deep learning scientist?

To thrive as a Deep Learning Scientist, you need a solid background in machine learning, statistics, and programming, often supported by an advanced degree in computer science or a related field. Familiarity with deep learning frameworks like TensorFlow or PyTorch, experience with cloud computing platforms, and proficiency in Python are typically required. Strong problem-solving skills, creativity, and the ability to communicate complex ideas clearly set outstanding candidates apart. These capabilities are essential for developing innovative AI solutions, interpreting results, and collaborating effectively in multidisciplinary teams.

What are some typical challenges faced when working as a deep learning scientist, and how can they be addressed?

Deep Learning Scientists often encounter challenges such as managing large datasets, tuning complex model architectures, and ensuring reproducibility of experiments. Handling these issues requires strong skills in data preprocessing, familiarity with version control systems, and experience with frameworks like TensorFlow or PyTorch. Collaborating closely with cross-functional teams—including data engineers, software developers, and domain experts—can also help in overcoming technical and project-related obstacles. Continuous learning and staying updated with the latest research is essential to excel in this rapidly evolving field.

What is the difference between Deep Learning Scientist vs Machine Learning Engineer?

AspectDeep Learning ScientistMachine Learning Engineer
Required CredentialsMaster's or PhD in Computer Science, Data Science, or related fields; strong background in deep learning frameworksBachelor's or Master's in Computer Science or related fields; proficiency in machine learning algorithms and software engineering
Work EnvironmentResearch-focused, experimental, often in R&D teamsDevelopment and deployment-focused, working on production systems
Employer & Industry UsageTech companies, research labs, AI startupsTech firms, finance, healthcare, and industries deploying ML models

While both roles involve machine learning, Deep Learning Scientists focus on developing advanced neural network models and research, whereas Machine Learning Engineers implement, optimize, and deploy these models in real-world applications.

What are popular job titles related to Deep Learning Scientist jobs in California?

For Deep Learning Scientist jobs in California, the most frequently searched job titles are:

What job categories do people searching Deep Learning Scientist jobs in California look for?

The top searched job categories for Deep Learning Scientist jobs in California are:

Infographic showing various Deep Learning Scientist job openings in California as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $121,131 per year, or $58.2 per hour.

Senior Machine Learning Scientist - Personalization

Expedia Group

San Jose, CA • On-site

Full-time

Medical, Dental, Vision, PTO

Re-posted 13 days ago


Expedia Group rating

6.9

Company rating: 6.9 out of 10

Based on 25 frontline employees who took The Breakroom Quiz

8th of 11 rated travel agencies


Job description

At Expedia Group, we help travelers explore the world, one journey at a time. As a global travel company powered by passionate people, trusted partnerships, and leading technology, we connect travelers, partners, and advertisers through our consumer brands, B2B network, and travel advertising business.
Here, you'll do meaningful work that helps millions of people discover, book, and experience travel with more ease, confidence, and joy. Our five Behaviors-Traveler First, Think Big, Operate with Excellence, Ownership Mindset, and Succeed Together-help foster a supportive environment where people can grow their careers and have the flexibility, benefits, and support to do their best work. Join us and build for travelers everywhere.
Senior Machine Learning Scientist - Personalization
Introduction to the team
The Unified Personalization Service team is part of Expedia Product & Technology. UPS is building Expedia Group's centralized, real-time personalization engine across brands and channels, powering ranking, recommendations, retrieval, and other adaptive experiences that help travelers see more relevant, contextual, and useful experiences throughout their journey.
We are looking for a Senior Machine Learning Scientist to help shape the next generation of deep learning systems for personalization, including recommendation, ranking, retrieval, traveler understanding, sequential modeling, and foundation-model-based personalization.
This is a senior hands-on applied science and engineering role for someone who can translate recent research into production-quality systems, influence technical direction, raise the modeling bar for the team, and mentor other scientists.
In this role, you will:
  • Design, develop, and apply machine learning solutions to real-world personalization, product, and business problems, translating ambiguous opportunities into scalable models, experiments, and production-ready capabilities

  • Drive end-to-end scientific work across problem formulation, data exploration, feature engineering, model development, evaluation, and iteration, with strong attention to measurable impact

  • Partner closely with engineers, product, and business stakeholders to integrate machine learning solutions into services and workflows, including system design, API design, and data modeling considerations where applicable

  • Use strong technical judgment to select appropriate methods, validate outcomes, and improve model performance, reliability, and operational quality across multiple problem domains

  • Safely integrate and operate AI/ML-enabled solutions that improve outcomes, including familiarity with AI-driven systems, tools, or workflows and applying AI/ML concepts to real world products

  • Contribute deep technical expertise across related domains, helping raise scientific and engineering quality through experimentation, documentation, mentoring, and reusable approaches that support broader team effectiveness

Minimum Qualifications:
  • Bachelor's degree in Computer Science or a related technical field; or Equivalent related professional experience

  • 8+ years of relevant professional experience

  • Demonstrated ownership of machine learning solutions at the service or multi-service level, including problem definition, model development, evaluation, and operationalization within a product or technical domain

  • Strong foundation in machine learning methods, statistical analysis, experimentation, and data-driven decision making, with hands-on coding experience in scientific and production-oriented environments

  • Experience working with cross-functional partners to deploy technical solutions, with core expectations in scalable model development, data modeling, and integration into software systems

Preferred Qualifications:
  • Advanced degree in Machine Learning, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field

  • Experience delivering machine learning solutions at scale, including architecture considerations, production monitoring, model lifecycle management, and operational excellence in live environments

  • Demonstrated ability to influence technical direction within a domain through rigorous experimentation, strong scientific reasoning, pragmatic solution design, and clear communication with cross-functional partners

  • Strong experience with recommendation, ranking, retrieval, search, personalization, ads, marketplace, e-commerce, or similarly complex applied ML systems

  • Experience with neural recommendation systems, sequential or session-based recommendation, transformer-based recommenders, semantic retrieval, generative retrieval, or representation learning at scale

  • Experience with foundation models, LLMs, embedding models, semantic IDs, hybrid LLM-recommender systems, two-stage retrieval and ranking systems, or retrieval-augmented personalization workflows

  • Relevant academic publications, patents, open-source contributions, technical blog posts, industry talks, or other contributions to the ML/recommender-systems community

The total cash range for this position in San Jose is $187,000.00 to $261,500.00. Employees in this role have the potential to increase their pay up to $299,000.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role.The total cash range for this position in Seattle is $173,000.00 to $242,500.00. Employees in this role have the potential to increase their pay up to $277,000.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role.
Starting pay for this role will vary based on multiple factors, including location, available budget, and an individual's knowledge, skills, and experience. Pay ranges may be modified in the future.
Benefits and perks
Expedia Group offers benefits and perks designed to support employees and their families, including medical, dental, and vision coverage, paid time off, an Employee Assistance Program, wellness and travel reimbursement, travel discounts, and International Airlines Travel Agent Network (IATAN) membership. Learn more about life at Expedia Group at https://careers.expediagroup.com/life.
Accommodation requests
Expedia Group is committed to providing an inclusive and accessible recruiting experience. If you need an accommodation or adjustment due to a disability during the application or recruiting process, please submit a request at https://expedia.service-now.com/askeg?id=job_accommodation.
About Expedia Group
Expedia Group includes three flagship consumer brands - Expedia, Hotels.com, and Vrbo - along with a leading B2B travel business and travel advertising offerings. Across our brands and business, we help travelers explore the world with confidence and ease.
Important notice
Employment opportunities and job offers at Expedia Group will always come from Expedia Group's Talent Acquisition and hiring teams. Never share sensitive personal information unless you are confident of the recipient. Expedia Group does not extend job offers via email or messaging tools to individuals with whom we have not made prior contact. Our email domain is @expediagroup.com. The official place to find and apply for roles is https://careers.expediagroup.com/jobs/.
Equal Opportunity
Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status, or any other characteristic protected by law. This employer participates in E-Verify. The employer will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee's I-9 to confirm work authorization.

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