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Applied Science Jobs in California (NOW HIRING)

Senior Applied Scientist

Los Angeles, CA ยท On-site +1

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

You will own the research and applied science agenda for personalization, from problem framing and data exploration through model development, evaluation, experimentation, and iteration. This role is ...

Senior Applied Scientist

Los Angeles, CA ยท On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

You will own the research and applied science agenda for personalization, from problem framing and data exploration through model development, evaluation, experimentation, and iteration. This role is ...

Senior Applied Scientist

San Jose, CA ยท On-site

$107K - $146K/yr

Adobe Firefly's Applied Science & Machine Learning (ASML) group invites an Applied Scientist / Machine Learning Engineer passionate about post-training and distillation of large generative AI models ...

Senior Applied Scientist

San Jose, CA

$107K - $146K/yr

Adobe Firefly's Applied Science & Machine Learning (ASML) group invites an Applied Scientist / Machine Learning Engineer passionate about post-training and distillation of large generative AI models ...

Senior Applied Scientist

San Jose, CA ยท On-site

$107K - $146K/yr

Partner with product management, applied science, and engineering to translate a fast-moving research literature into shipping product features. What you need to succeed * Substantial hands-on ...

Senior Applied AI Engineer

San Francisco, CA ยท On-site

$211K - $235K/yr

About Alembic Alembic is an applied science company building GPU-resident distributed data systems that deliver 10-100x performance for Fortune 500 clients including NVIDIA and Delta. We're Series B ...

Senior Applied Scientist

San Jose, CA

$107K - $146K/yr

Partner with product management, applied science, and engineering to translate a fast-moving research literature into shipping product features. What you need to succeed * Substantial hands-on ...

Showing results 41-60

Applied Science information

See California salary details

$24.2K

$47.8K

$78K

How much do applied science jobs pay per year?

As of Aug 18, 2026, the average yearly pay for applied science in California is $47,757.00, according to ZipRecruiter salary data. Most workers in this role earn between $38,000.00 and $51,300.00 per year, depending on experience, location, and employer.

What is an applied science?

An Applied Science job involves using scientific principles and methodologies to solve real-world problems in various industries, such as technology, healthcare, and engineering. Professionals in this field apply research, data analysis, and experimentation to develop practical solutions and improve processes. These roles often require collaboration with engineers, product teams, and business stakeholders to implement innovations effectively.

What are the key skills and qualifications needed to thrive in the applied science position, and why are they important?

To excel in Applied Science, a strong background in mathematics, statistics, computer science, and domain-specific scientific knowledge is essential, typically supported by a relevant advanced degree. Familiarity with data analysis tools (such as Python, R, MATLAB), machine learning frameworks, and experience with statistical modeling or experimental design are highly valued. Critical thinking, problem-solving abilities, and effective communication skills are important soft skills for translating scientific insights into practical solutions. These skills and qualities are crucial for driving innovation, collaboration, and the successful application of scientific methods to solve complex, real-world problems.

What are some common challenges faced by professionals in applied science roles?

Professionals in Applied Science often encounter the challenge of translating complex data or scientific concepts into actionable business solutions that non-experts can understand and implement. Balancing rigorous scientific methodology with the practical constraints of project deadlines and stakeholder expectations is also common. Working cross-functionally with teams in engineering, product management, or business operations requires ongoing collaboration and clear communication. Successfully navigating these challenges helps ensure the impact and relevance of applied scientific work within an organization.

Is applied science a good career choice?

Applied science is a viable career path that involves using scientific principles to develop practical solutions and technologies. It often requires strong problem-solving skills, technical knowledge, and may involve working in research, development, or engineering environments. Job prospects can vary based on industry demand and specialization areas.

What careers use applied science?

Applied science careers include roles such as biomedical engineers, environmental scientists, data analysts, and laboratory technicians. These jobs often require strong problem-solving skills, knowledge of scientific principles, and proficiency with tools and technology relevant to the field.

What does an applied science do?

An applied science professional uses scientific principles and methods to develop practical solutions, products, or technologies in fields such as engineering, healthcare, or environmental management. They often work in laboratories, research facilities, or industry settings, applying skills in data analysis, experimentation, and technical tools to address real-world problems.

What are the most commonly searched types of Applied Science jobs in California?

The most popular types of Applied Science jobs in California are:

What job categories do people searching Applied Science jobs in California look for?

The top searched job categories for Applied Science jobs in California are:

What cities in California are hiring for Applied Science jobs?

Cities in California with the most Applied Science job openings:

Infographic showing various Applied Science job openings in California as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 17% Part Time, and 2% Contract. Highlights an 73% Physical, 4% Hybrid, and 23% Remote job distribution, with an average salary of $47,757 per year, or $23 per hour.

Director of Applied AI/ML Science - Ads

Faire

San Francisco, CA โ€ข On-site

$276K - $379K/yr

Full-time

Re-posted 4 days ago


Job description

About this Role

Ads is one of the fastest-growing and most strategically important parts of Faire's business, and the Ads Data team - now three years old - is entering a period of hypergrowth. As Director of Data for Ads, you will own the end-to-end data vision and strategy for the Ads business - from the applied science and ML powering our marketplace to the data foundation underneath it.

You'll lead and grow a team spanning Applied Scientists and Analytics/Data Engineers, set the technical vision and roadmap for the group, and partner closely with cross-functional leaders in Product, Engineering, Design, and Strategy & Analytics (S&A) to define how the Ads org operates - its planning cadence, prioritization framework, and execution rigor. This is a rare opportunity to shape, from an early stage, the technical and organizational backbone of one of Faire's most important growth engines.

What You'll Do

  • Define the holistic data vision and strategy for Ads, spanning retrieval/ranking ML (search ads relevance, query understanding, personalization), bidding/marketplace/auction systems (auction design, bid optimization, pacing, budget allocation, advertiser ROI), and data engineering/ETL (pipelines, data foundations, and analytics that power decision-making across the org).
  • People-manage and grow the full group of Applied Scientists and Analytics Engineers on the Ads Data team - hiring, mentoring, setting career development paths, and building a strong technical culture as the team scales through hypergrowth.
  • Own the team's long-term technical roadmap, ensuring it's tightly aligned to company and Ads org strategy, and translate that roadmap into clear priorities, staffing plans, and execution.
  • Partner with cross-functional leaders to design and run the team's operating model - planning cadence, prioritization frameworks, roadmap reviews, and cross-team rituals - so Ads Data operates as a high-leverage, well-run function as it grows.
  • Drive significant business impact through hands-on contribution to high-priority ML/algorithmic problems when needed, while building the team's ability to deliver this work independently and at scale.
  • Serve as a key member of the broader Data leadership team, contributing to how the data org is built and run - both technically (architecture, tooling, standards) and organizationally (processes, career frameworks, hiring bar).
  • Represent Ads Data in company-level strategic conversations, ensuring data and ML considerations are embedded early in product and business planning.

Qualifications

  • 8+ years of experience in data science, applied ML, or ML engineering roles, ideally with exposure to ads, search, recommendation systems, marketplaces, or auctions.
  • 4+ years of experience managing technical teams of 5+ people, including senior ICs.
  • Direct experience with ads marketplaces, auction systems, or search/recommendation systems.
  • Demonstrated ability to set technical vision and strategy for a team or org, and to translate that strategy into roadmaps, priorities, and measurable outcomes.
  • Comfort operating across a broad technical surface area - from ML modeling (bidding, auction, ranking, relevance) to data engineering and analytics infrastructure - with enough depth to earn credibility with ICs across all of these areas.
  • Strong track record partnering with cross-functional partners to define team operating models and drive cross-functional execution.
  • Excellent communication skills, with the ability to flex between technical depth and business-level narrative depending on the audience.
  • Comfort with ambiguity and rapid change - this team is young and growing fast, and the role requires building process and structure while the ground is still shifting.

Great to Haves

  • Academic background in Computer Science, Machine Learning, Statistics, Math, Operations Research, or a related field; PhD a plus.
  • Prior experience building or scaling a data/applied science org from an early stage.

Salary Range

San Francisco: the pay range for this role is $276,000 to $379,500 per year.ย 

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.