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Scientific Machine Learning Jobs in California (NOW HIRING)

Machina Labs

Machine Learning Engineer

Los Angeles, CA

$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 ...

Doist

Machine Learning Engineer

South San Francisco, CA · On-site

$212 - $318/hr

Must have a Bachelor's degree or foreign equivalent in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field, plus two (2) years of experience in Building and ...

New

Spotter

Machine Learning Scientist

Culver City, CA · On-site

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 reinforcement ...

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 · 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.

Pattern AI

Machine Learning Engineer

San Mateo, CA · On-site

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.

Unitytech

Machine Learning Engineer

San Francisco, CA · On-site +1

$117K - $152K/yr

Bachelor's degree in Computer Science, Machine Learning, Systems, or a related field * Strong foundation in machine learning systems, distributed systems, or large-scale data processing (through ...

Unitytech

Machine Learning Engineer

Mountain View, CA · On-site +1

$117K - $152K/yr

Bachelor's degree in Computer Science, Machine Learning, Systems, or a related field * Strong foundation in machine learning systems, distributed systems, or large-scale data processing (through ...

Tapestry

Machine Learning Engineer

Mountain View, CA · On-site

You will work closely with other Machine Learning Engineers, Data Scientists and Software Engineers across diverse ML domains spanning multimodal machine learning, information retrieval, natural ...

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All JobsScientific Machine Learning JobsScientific Machine Learning Jobs in California

Scientific Machine Learning information

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 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 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.

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.

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 August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 18% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Machine Learning Engineer

Machina Labs

Los Angeles, CA

$160K - $190K/yr

Full-time

Re-posted 9 days ago

Job description

About Machina Labs
 
Engineering moves at software speed. Manufacturing doesn't. Yet.
 
Machina Labs is changing that. We build intelligent, software-defined factories that produce complex metal structures directly from digital design. By integrating advanced metal forming, robotics, and automated production inside a flexible factory architecture, we enable customers to move from prototype to production in weeks, not years.
 
Backed by Lockheed Martin, Toyota, and NVIDIA, we're building the manufacturing infrastructure that defense, aerospace, and advanced mobility programs will run on.
 
If you want to work on hard problems that matter and see them fly, drive, and defend, this is the place.    

Job Description:

We are looking for a Machine Learning Engineer to join our team and help us push the boundaries of what’s possible in smart manufacturing. In this role, you will design, build, train, and deploy machine learning models that power our robotic sheet metal forming systems. You’ll work closely with our engineering team to transform raw data into actionable intelligence, enabling our robots to produce parts with greater precision, speed, and adaptability.

This is a hands-on role for someone who thrives at the intersection of research and production, someone who is just as comfortable wrangling messy datasets as they are architecting scalable ML pipelines. If you’re passionate about applying machine learning to real-world manufacturing challenges, we’d love to hear from you.

Key Responsibilities:
  • Design, build, train, evaluate, and deploy machine learning models to support and improve our robotic manufacturing processes.
  • Identify, collect, clean, and organize data from diverse sources to construct high-quality datasets for model training and evaluation.
  • Develop and maintain scalable ML pipelines and infrastructure using cloud platforms, with a focus on Azure.
  • Leverage Databricks and Apache Spark for large-scale data processing and model development.
  • Collaborate with cross-functional teams, including robotics, software, and manufacturing engineers to integrate ML solutions into production workflows.
  • Stay current with the latest developments in machine learning and AI and evaluate their applicability to our manufacturing challenges.
  • Write clean, well-documented, and production-quality Python code.
  • Communicate findings, results, and recommendations to both technical and non-technical stakeholders.
  • Stay current with the latest developments in machine learning and AI and evaluate their applicability to our manufacturing challenges.
  • Write clean, well-documented, and production-quality Python code.
  • Communicate findings, results, and recommendations to both technical and non-technical stakeholders.
Required Background & Experience:
  • 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 field with 3+ years of experience.
  • Strong experience designing, building, training, and testing machine learning models end-to-end.
  • Proven ability to work with raw, unstructured, or incomplete data, including data collection, cleaning, labeling, and dataset construction.
  • Proficiency in Python for ML development, data processing, and scripting.
  • Familiarity with cloud computing frameworks and services, with a preference for Microsoft Azure.
  • Experience with Databricks and Apache Spark for data engineering and model development.
Preferred Qualifications:
  • Machine learning experience in CAD and computational geometry applications.
  • Experience working in the industrial or manufacturing space.
  • Experience with robotics, including robotic perception, control, or planning.
 

*This job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities required for this role. Duties and responsibilities may change based on business needs.

The base salary range for this role is dependent on experience, qualifications, and overall alignment with the scope of the position.

In addition to base compensation, Machina Labs offers a competitive benefits package and stock option participation.

 
Machina Labs is an Affirmative Action and Equal Employment Opportunity employer and considers all applicants for employment without regard to race, color, religion, sex, gender identity, gender expression, sexual orientation, national origin, age, disability, or status as a protected veteran in accordance with state and federal law. 
 
We endeavor to make the job application process accessible to any and all users. If you have a disability that impacts your ability to complete the job application process and would like to request assistance or a reasonable accommodation, please contact us at (888)444-9777. This contact information is for accommodation requests only, not to inquire about the status of applications.

*This job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities required for this role. Duties and responsibilities may change based on business needs. 

Machina Labs is an Affirmative Action and Equal Employment Opportunity employer and considers all applicants for employment without regard to race, color, religion, sex, gender identity, gender expression, sexual orientation, national origin, age, disability, or status as a protected veteran in accordance with state and federal law. 

We endeavor to make the job application process accessible to any and all users. If you have a disability that impacts your ability to complete the job application process and would like to request assistance or a reasonable accommodation, please contact us at (888)444-9777. This contact information is for accommodation requests only, not to inquire about the status of applications.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.