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Scientific Machine Learning Jobs in California (NOW HIRING)

Spotter

Machine Learning Scientist

Culver City, CA · Remote

Overview We're looking for a talented and intensely curious Machine Learning Scientist with deep expertise in building and deploying production machine learning models, particularly in areas such as ...

Machina Labs

Machine Learning Engineer

Chatsworth, CA · On-site

$160K - $190K/yr

Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a closely related field with 6+ years of hands-on experience in machine learning and AI; or a Ph.D. in a relevant ...

Spotter

Machine Learning Scientist

Culver City, CA · On-site

For more information about Spotter, please visit Overview We're looking for a talented and intensely curious Machine Learning Scientist with deep expertise in building and deploying production ...

Pattern AI

Machine Learning Engineer

San Mateo, CA

Qualifications Experience: * 3+ years of professional experience as a Machine Learning Engineer or production-focused Data Scientist. * Proficiency across topics in machine learning and statistics.

Pattern AI

Machine Learning Engineer

San Mateo, CA · On-site +1

Qualifications Experience: * 3+ years of professional experience as a Machine Learning Engineer or production-focused Data Scientist. * Proficiency across topics in machine learning and statistics.

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Scientific Machine Learning information

Is ML a high paying job?

Scientific Machine Learning roles typically offer high salaries due to the specialized skills required, such as expertise in deep learning, data analysis, and programming with tools like Python and TensorFlow. Compensation varies by industry, experience, and location but generally exceeds average tech salaries for comparable roles.

Which 3 jobs will survive AI?

Scientific Machine Learning professionals will likely continue to be in demand due to their expertise in developing and applying AI models to complex scientific problems. Roles such as data scientists, AI researchers, and machine learning engineers are expected to persist because they require specialized knowledge, critical thinking, and ongoing innovation that AI tools complement rather than replace. These jobs often involve interdisciplinary skills, programming, and understanding of domain-specific data, making them more resilient to automation.

What is scientific machine learning?

Scientific machine learning (SciML) is an interdisciplinary field that combines principles from machine learning and scientific computing to solve complex scientific and engineering problems. It involves developing algorithms and models that can learn from data and physical laws, such as differential equations, to make predictions, optimize systems, or gain insights into phenomena. SciML is widely used in areas like physics, biology, climate science, and engineering, enabling researchers to accelerate simulations and make data-driven discoveries. The field often leverages both traditional numerical methods and modern machine learning techniques, making it a rapidly evolving area of research.

What are some common challenges faced by professionals in Scientific Machine Learning, and how can they be addressed?

Professionals in Scientific Machine Learning often encounter challenges such as integrating domain-specific scientific knowledge with machine learning models, managing large and complex datasets, and ensuring that models are interpretable and physically consistent. Collaboration with domain experts and interdisciplinary teams is essential to bridge knowledge gaps and validate results. To address these challenges, it is helpful to invest time in understanding the underlying scientific principles, keep up-to-date with advancements in both machine learning and scientific fields, and utilize specialized tools and frameworks designed for scientific data.

How much does a machine learning scientist make?

A machine learning scientist typically earns between $90,000 and $150,000 annually, depending on experience, education, and location. Senior roles or those with specialized skills in deep learning or natural language processing can earn higher salaries, often exceeding $180,000.

What are the key skills and qualifications needed to thrive as a Scientific Machine Learning professional, and why are they important?

To thrive as a Scientific Machine Learning professional, you need a strong background in mathematics, statistics, programming (often Python), and domain-specific scientific knowledge, typically with a graduate degree in a STEM field. Proficiency in machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools (like NumPy, SciPy), and experience with high-performance computing are commonly required. Critical thinking, problem-solving, and collaborative communication are vital soft skills for designing experiments and interpreting complex data. These skills ensure robust, reproducible results and the ability to bridge scientific inquiry with advanced computational methods.

What is the difference between Scientific Machine Learning vs Data Scientist?

AspectScientific Machine LearningData Scientist
Required credentialsAdvanced degrees in CS, ML, or related fields; knowledge of scientific computingDegree in CS, statistics, or related fields; strong analytical skills
Work environmentResearch labs, academia, industry R&D teamsBusiness analytics, tech companies, consulting firms
Industry usageResearch, scientific computing, engineering simulationsBusiness insights, predictive modeling, data analysis

Scientific Machine Learning focuses on integrating scientific knowledge with machine learning techniques for research and engineering applications. Data Scientists analyze data to extract insights and build predictive models for business or operational purposes. While both roles require strong technical skills, Scientific Machine Learning emphasizes scientific computing and domain-specific modeling, whereas Data Scientists focus on data analysis and visualization.

Is 40 too late for data science?

Scientific Machine Learning roles often value skills and experience over age, and many professionals transition into data science or machine learning at various stages of their careers. Learning relevant tools like Python, TensorFlow, or scikit-learn and gaining practical experience can help regardless of age, making 40 not too late to pursue this field.
What are popular job titles related to Scientific Machine Learning jobs in California? For Scientific Machine Learning jobs in California, the most frequently searched job titles are:
What job categories do people searching Scientific Machine Learning jobs in California look for? The top searched job categories for Scientific Machine Learning jobs in California are:
What cities in California are hiring for Scientific Machine Learning jobs? Cities in California with the most Scientific Machine Learning job openings:
Scientific Machine Learning jobs near you
Infographic showing various Scientific Machine Learning job openings in California as of June 2026, with employment types broken down into 3% As Needed, 72% Full Time, 19% Part Time, 3% Temporary, and 3% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution.
AI / Machine Learning Talent

AI / Machine Learning Talent

Ensemble Health Partners, Inc.

San Jose, CA • On-site

Full-time

Medical, Retirement

Posted 8 days ago

Ensemble Health Partners rating

6.5

Company rating: 6.5 out of 10

Based on 239 frontline employees who took The Breakroom Quiz

137th of 146 rated financial services

Job description

Thank you for considering a career at Ensemble!
Ensemble is a leading provider of technology-enabled revenue cycle management solutions for health systems, including hospitals and affiliated physician groups. They offer end-to-end revenue cycle solutions as well as a comprehensive suite of point solutions to clients across the country.
Ensemble keeps communities healthy by keeping hospitals healthy. We recognize that healthcare requires a human touch, and we believe that every touch should be meaningful. This is why our people are the most important part of who we are. By empowering them to challenge the status quo, we know they will be the difference!
O.N.E Purpose:
  • Customer Obsession: Consistently provide exceptional experiences for our clients, patients, and colleagues by understanding their needs and exceeding their expectations.
  • Embracing New Ideas: Continuously innovate by embracing emerging technology and fostering a culture of creativity and experimentation.
  • Striving for Excellence: Execute at a high level by demonstrating our "Best in KLAS" Ensemble Difference Principles and consistently delivering outstanding results.

The Opportunity:
AI Lab - AI/ML Opportunities
Location: San Jose, CA (Hybrid - Onsite 3x per week on Tues, Wed, Thurs)
About Ensemble's AI Lab
Ensemble Health Partners is the leading Revenue Cycle Management (RCM) partner to U.S. health systems. We sit between hospitals, payers, and patients, and we are responsible for billions of dollars of healthcare revenue moving accurately and on time. AI is increasingly central to how we do that work - from predicting denials and automating coding to flagging payment integrity issues and routing accounts to the right action at the right time. These roles exists where those AI systems meet the business outcomes we are paid to deliver.
We are continuously building a pipeline of exceptional AI/ML talent across research, data science, and engineering. This general application allows candidates to be considered for multiple roles across the AI Lab. Final role alignment (e.g., Data Scientist, AI Research Scientist, Machine Learning Engineer) and leveling will be determined based on interview performance, experience, and team needs.
What You'll Work On
Depending on your background and strengths, you may:
  • Design, build, evaluate, and improve machine learning and AI systems in production environments
  • Translate business problems into AI/ML solutions and measurable outcomes
  • Develop and run experiments to evaluate models, including defining metrics, datasets, and success criteria
  • Productize models into scalable, reliable, and cost-efficient services
  • Optimize training and inference performance (latency, throughput, cost)
  • Analyze real-world system behavior and production data to drive continuous improvements
  • Partner cross-functionally with engineering, product, and domain experts to deliver end-to-end solutions
  • Contribute to AI research, experimentation, and adoption of new techniques where applicable
  • Communicate findings, tradeoffs, and recommendations clearly to both technical and non-technical stakeholders

What We're Looking For
We are hiring across a range of profiles, but strong candidates will demonstrate:
  • Proven experience working with machine learning or AI systems in real-world or production settings
  • Strong problem-solving skills and ability to operate in ambiguous, evolving environments
  • Ability to connect technical work to measurable business or product outcomes
  • Experience collaborating across teams (engineering, product, data, or research)
  • Ownership mindset-taking work from idea through execution and impact

Technical Skills (vary by role)
Candidates may have experience with some combination of:
  • Programming: Python (required), plus familiarity with SQL and other languages (e.g., Java, C++, Go)
  • Machine Learning: Model development, evaluation, and optimization
  • Deep Learning: Frameworks such as PyTorch, TensorFlow, Hugging Face
  • LLMs & Modern AI: Fine-tuning, prompt engineering, evaluation frameworks, or emerging techniques (e.g., PEFT, RLHF)
  • Data & Analytics: Statistics, experimentation, causal inference, and working with real-world datasets
  • Systems & Infrastructure (Engineer-leaning candidates):
    • Model serving, APIs, and distributed systems
    • Training at scale (e.g., multi-GPU / distributed training)
    • Performance optimization and cost efficiency
  • Research (Research-leaning candidates):
    • Experiment design, evaluation rigor
    • Reading and applying state-of-the-art research
    • Publication or novel contributions (preferred, not required)

Qualifications
  • Bachelor's degree in Computer Science, Engineering, Data Science, Mathematics, or related field required
  • Master's or PhD preferred for certain roles (especially research-oriented positions), but not required for all paths
  • Relevant industry experience typically ranges from 3+ years (Senior) to advanced leadership/ownership experience (Staff/Principal)

The base salary range for these roles is $154,100 to $341,600.
Join an award-winning company
Five-time winner of "Best in KLAS" 2020-2022, 2024-2025
Black Book Research's Top Revenue Cycle Management Outsourcing Solution 2021-2024
22 Healthcare Financial Management Association (HFMA) MAP Awards for High Performance in Revenue Cycle 2019-2024
Leader in Everest Group's RCM Operations PEAK Matrix Assessment 2024
Clarivate Healthcare Business Insights (HBI) Revenue Cycle Awards for strong performance 2020, 2022-2023
Energage Top Workplaces USA 2022-2024
Fortune Media Best Workplaces in Healthcare 2024
Monster Top Workplace for Remote Work 2024
Great Place to Work certified 2023-2024
  • Innovation
  • Work-Life Flexibility
  • Leadership
  • Purpose + Values

Bottom line, we believe in empowering people and giving them the tools and resources needed to thrive. A few of those include:
  • Associate Benefits - We offer a comprehensive benefits package designed to support the physical, emotional, and financial health of you and your family, including healthcare, time off, retirement, and well-being programs.
  • Our Culture - Ensemble is a place where associates can do their best work and be their best selves. We put people first, last and always. Our culture is rooted in collaboration, growth, and innovation.
  • Growth - We invest in your professional development. Each associate will earn a professional certification relevant to their field and can obtain tuition reimbursement.
  • Recognition - We offer quarterly and annual incentive programs for all employees who go beyond and keep raising the bar for themselves and the company.

Ensemble is an equal employment opportunity employer. It is our policy not to discriminate against any applicant or employee based on race, color, sex, sexual orientation, gender, gender identity, religion, national origin, age, disability, military or veteran status, genetic information or any other basis protected by applicable federal, state, or local laws. Ensemble also prohibits harassment of applicants or employees based on any of these protected categories.
Ensemble provides reasonable accommodations to qualified individuals with disabilities in accordance with the Americans with Disabilities Act and applicable state and local law. If you require accommodation in the application process, please contact TA@ensemblehp.com.
This posting addresses state specific requirements to provide pay transparency. Compensation decisions consider many job-related factors, including but not limited to geographic location; knowledge; skills; relevant experience; education; licensure; internal equity; time in position. A candidate entry rate of pay does not typically fall at the minimum or maximum of the role's range.
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