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Applied Scientist Machine Learning Jobs in California

Senior Applied Scientist

Mountain View, CA ยท On-site +1

$144K - $236K/yr

LinkedIn's Data Science and Applied Science teams use data, experimentation, causal inference, machine learning, and AI to solve important product and business problems. With more than 1 billion ...

Senior Applied Scientist

Mountain View, CA ยท On-site

$144K - $236K/yr

LinkedIn's Data Science and Applied Science teams use data, experimentation, causal inference, machine learning, and AI to solve important product and business problems. With more than 1 billion ...

Applied Scientist (ML)

Mountain View, CA ยท Hybrid

$190K - $275K/yr

PhD or Master's degree in Computer Science, Machine Learning, NLP, or a related field * Strong ... industry applied ML research environment * Familiarity with retrieval-augmented generation ...

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 ...

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 ...

Machine Learning Engineer

Santa Clara, CA ยท On-site

$150K - $277K/yr

Mentor aspiring applied scientists and engineers to broaden their horizons and amplify their impact ... Machine Learning, Information Retrieval, Data Science or related field or equivalent work ...

Applied Scientist III Job Location: Santa Clara, California Job Number: AMZ10362489 Position ... Master's degree or foreign equivalent degree in Computer Science, Machine Learning, Engineering, or ...

Showing results 41-60

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 Sep 14, 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 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.

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 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.

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:

Infographic showing various Applied Scientist Machine Learning job openings in California as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 73% Full Time, 22% Part Time, 1% Temporary, and 2% Contract. Highlights an 82% Physical, 2% Hybrid, and 16% Remote job distribution, with an average salary of $127,000 per year, or $61.1 per hour.

Machine Learning Scientist, BioML

Emeryville, CA โ€ข On-site

Other

Medical, Dental, Vision, Retirement, PTO

This job post hasย expired today.ย Applications are no longer accepted.


Job description

Profluent is an AI-first protein design company. Founded in 2022, we develop deep generative models to design and validate novel, functional proteins to revolutionize biomedicine. Based in Emeryville, CA, we are backed by leading investors including Altimeter Capital, Bezos Expeditions, Spark Capital, Insight Partners, Air Street Capital, AIX Ventures, and Convergent Ventures, and have raised over $150M to date.

We're looking for a motivated and creative Machine Learning (ML) Scientist to drive research into models at the intersection of complex protein biology and AI. This position offers an opportunity to work at the forefront of generative modeling research across language processing, representation learning, and protein engineering. You should be a self-directed researcher who has the ability to rapidly prototype and evaluate new models and algorithms in the biomolecular domain.

As an early employee, you will proactively shape the direction of our machine learning efforts and collaborate across diverse teams of computational and experimental scientists.

Responsibilities
  • Design and develop state-of-the-art predictive and generative models incorporating domain-specific evolutionary and experimental data
  • Leverage massive-scale protein and nucleic acid data to train specialized models for protein understanding and design
  • Curate relevant datasets and design tasks for rigorous evaluation of generative models
  • Collaborate across the machine learning and protein design teams to adapt and apply techniques for experimental validation
  • Implement, analyze, and interpret multiple computational approaches and present results to colleagues in regular update meetings
  • Work within a collaborative, fast-paced, interdisciplinary team across biology and machine learning to help shape the scientific and strategic vision of the company
Qualifications
  • PhD (or equivalent industry experience) in Computer Science, Machine Learning, Natural Language Processing, Applied Math, Computational Biology, Statistics, or a related field
  • Experience with conceiving of, implementing, and evaluating novel machine learning techniques at the intersection with biology
  • Publications at major machine learning conferences (NeurIPS, ICML, ICLR) or scientific journals (Nature, Science, Nature Biotech, Nature Methods, PNAS)
  • Experience with modern deep learning frameworks such as Pytorch or Jax
Preferences
  • Familiarity with foundational biology of proteins and nucleic acids
  • Experience developing machine learning models for proteins (language models, structure prediction, design)
  • Experience with cloud compute platforms (GCP, AWS, Azure, OCI)
  • Previous experience in data extraction and curation from bioinformatics data sources
  • Familiarity with wet lab experimental assays and associated limitations
  • 3 to 5 years of industry experience
What We Offer
  • High-growth opportunity with meaningful impact on the future of protein design
  • Competitive compensation package with equity participation
  • 401(k) with a strong employer match
  • Comprehensive benefits including health/dental/vision insurance
  • Generous PTO policy and commitment to work-life balance
  • Professional development opportunities in a cutting-edge field at the intersection of AI and biology
Employment Eligibility Verification

Legal authorization to work in the United States is required. In compliance with federal law, all persons hired must verify their identity and work eligibility and complete the required employment verification form upon hire.

Profluent Bio, Inc is an equal opportunity employer promoting diversity and inclusion in the workspace. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical conditions, veteran status, sexual orientation, gender (including gender identity and gender expression), sex (which includes pregnancy, childbirth, and breastfeeding), genetic information, taking or requesting statutorily protected leave, or any other basis protected by law.

Hiring Salary Range

200,000 - 330,000 USD

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