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Machine Learning Researcher Jobs in Berkeley, CA

Winaxis

Machine Learning Engineer

Fremont, CA · On-site

Machine Learning Engineer Location: Fremont, CA (Local) Onsite interview Duration: 12+ Mos H1B Only ... Write clean, modular, and sustainable code to translate research ideas into production-ready ...

S27a

Machine Learning Engineer

San Francisco, CA · On-site

$140 - $210/hr

Research, design, and implement machine learning algorithms to optimize workflow automation. * Develop, test, and modify computer programs to apply machine learning models to real-world applications.

PROPRIUS

Machine Learning Engineer

San Francisco, CA

Machine Learning Engineer Location: San Francisco, CA Sponsorship: No Relocation: No Industry ... Become part of a collaborative team that tackles research problems through a process of prototyping ...

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Showing results 21-40

All JobsMachine Learning Researcher JobsMachine Learning Researcher Jobs in Berkeley, CA

Machine Learning Researcher information

See Berkeley, CA salary details

$36.7K

$138.5K

$201.4K

How much do machine learning researcher jobs pay per year?

As of Aug 20, 2026, the average yearly pay for machine learning researcher in Berkeley, CA is $138,486.00, according to ZipRecruiter salary data. Most workers in this role earn between $82,000.00 and $188,600.00 per year, depending on experience, location, and employer.

What does a machine learning researcher do?

A Machine Learning Researcher designs, develops, and tests algorithms and models that allow computers to learn from and make decisions based on data. They often work on advancing the field by exploring new methods, improving existing algorithms, and publishing their findings. These researchers collaborate with engineers and data scientists to apply their research to practical problems in areas like computer vision, natural language processing, and robotics. Their work typically involves a combination of mathematics, statistics, programming, and experimentation.

What are the key skills and qualifications needed to thrive as a machine learning researcher?

To thrive as a Machine Learning Researcher, you need deep expertise in mathematics, statistics, programming (typically Python), and a strong academic background in computer science or related fields. Familiarity with frameworks like TensorFlow or PyTorch and experience with tools for data analysis and model development are standard, often supported by advanced degrees or relevant certifications. Critical thinking, creativity, and effective communication are vital soft skills for developing novel solutions and collaborating across interdisciplinary teams. These skills enable researchers to design innovative algorithms, validate models rigorously, and contribute impactful advancements in the field.

What are some common challenges machine learning researchers face when transitioning from academic research to industry roles?

Machine Learning Researchers often find that transitioning to industry involves adapting to faster project timelines, collaborative workflows, and a focus on scalable, real-world solutions rather than theoretical advances alone. In industry, you'll likely work closely with cross-functional teams, such as software engineers and product managers, to ensure models are both practical and maintainable. Balancing innovation with business objectives, handling production constraints, and communicating complex findings to non-technical stakeholders are some of the key challenges you may encounter.

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

AspectMachine Learning ResearcherData Scientist
Required CredentialsAdvanced degrees in CS, ML, or related fields; research experienceDegree in CS, statistics, or related; strong analytical skills
Work EnvironmentResearch labs, academia, R&D departmentsBusiness environments, tech companies, consulting
Employer & Industry UsageUniversities, research institutions, tech firmsCorporations, startups, finance, healthcare
Common Search & ComparisonFocus on theoretical ML advancementsFocus on data analysis & business insights

While both roles involve working with data and algorithms, Machine Learning Researchers primarily focus on developing new algorithms and advancing ML theory, often in research or academic settings. Data Scientists apply these techniques to analyze data, generate insights, and support business decisions in industry environments.

What are popular job titles related to Machine Learning Researcher jobs in Berkeley, CA?

For Machine Learning Researcher jobs in Berkeley, CA, the most frequently searched job titles are:

What job categories do people searching Machine Learning Researcher jobs in Berkeley, CA look for?

The top searched job categories for Machine Learning Researcher jobs in Berkeley, CA are:

What cities near Berkeley, CA are hiring for Machine Learning Researcher jobs?

Cities near Berkeley, CA with the most Machine Learning Researcher job openings:

Machine Learning Researcher jobs near you
Infographic showing various Machine Learning Researcher job openings in Berkeley, CA as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 21% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $138,486 per year, or $66.6 per hour.

Machine Learning Research Scientist

Blank Bio

San Francisco, CA • On-site

Full-time

Re-posted 3 days ago

Job description

Job Summary:
Blank Bio is an applied AI research lab focused on increasing the success rates of clinical trials through innovative RNA foundation models. The Machine Learning Research Scientist will design novel ML methods and develop evaluation benchmarks to enhance diagnostic and treatment processes in clinical trials.
Responsibilities:
• Design and prototype new ML methods (representation learning, generative modeling, contrastive pretraining) for RNA biology.
• Develop benchmarks and evaluation frameworks for tasks spanning diagnostics, patient stratification, biomarker discovery, and more
• Analyze large-scale sequencing datasets (bulk RNA-seq, single-cell, long-read) to inform model development and evaluation.
Qualifications:
Required:
• PhD (or equivalent experience) in Machine Learning, Computational Biology, or related fields.
• Demonstrated track record in ML research (publications, impactful projects, or deployed systems).
• Expertise in representation learning, and/or large-scale sequence modeling.
• Ability to independently design and execute research projects.
Preferred:
• Familiarity with transcriptomics, RNA biology, or other -omics data.
• Experience developing benchmarks for biological or clinical ML tasks.
• Prior collaboration with clinical researchers, diagnostic developers, or biomarker discovery teams.
• Previous work in an early-stage, fast-paced environment.
Company:
Blank Bio is an applied AI research company developing RNA foundation models that analyze biological sequence data for therapeutic research. Founded in 2025, the company is headquartered in San Francisco, USA, with a team of 2-10 employees. The company is currently Early Stage.

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