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Machine Learning Researcher Jobs in Berkeley, CA

Machine Learning Researcher

San Francisco, CA · On-site

$140K - $250K/yr

  • Medical

About the Role We are looking for a talented Machine Learning Researcher to join our core R&D team. You will design and implement advanced machine learning models for EEG-based neural decoding ...

Conduct research using machine learning methodologies that integrate financial theory with deep learning and reinforcement learning * Design and develop models that convert AI-extracted signals from ...

Conduct research using machine learning methodologies that integrate financial theory with deep learning and reinforcement learning * Design and develop models that convert AI-extracted signals from ...

MSCI is establishing a Machine Learning Center of Excellence within the Research & Development team to develop machine learning models that power investment tools for institutional clients. We are ...

Machine Learning Researcher

San Francisco, CA · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • PTO

As a Machine Learning Researcher, you will play a pivotal role in pushing the boundaries of what's possible with AI in education. Your work will assist teachers by personalizing their teaching ...

Machine Learning Researcher, Audio

San Francisco, CA · On-site

$160 - $250/hr

  • Medical

  • Dental

  • Vision

Machine Learning Researcher, Audio Location: San Francisco, CA or Remote (US) About Bland At Bland.com, our mission is to empower enterprises to build AI phone agents at scale. Based in San Francisco ...

Machine Learning Researcher, Audio

San Francisco, CA · On-site

$140K - $250K/yr

  • Medical

  • Dental

  • Vision

Machine Learning Researcher, Audio Location: San Francisco, CA or Remote About Bland At Bland.com, our mission is to empower enterprises to build AI phone agents at scale. Based in San Francisco, we ...

Perform reinforcement learning research to improve model alignment and capability * Develop and improve our distillation pipeline for training high-quality models from frontier teachers * Train ...

Perform reinforcement learning research to improve model alignment and capability * Develop and improve our distillation pipeline for training high‑quality models from frontier teachers * Train ...

New

We are looking for an ML researcher who will be responsible for designing, training, and testing data pipelines and ML models while collaborating with current developers on existing models and ...

New

Machine Learning Engineer

San Mateo, CA · On-site

$110 - $165/hr

  • Medical

  • Dental

  • Vision

  • PTO

Machine Learning Engineer / Research Engineer Pay: $$110,000 - $165,000 Base Salary + Equity Shift: N/A Location: San Mateo, CA (Peninsula) - Onsite Preferred Schedule: Full time, Permanent Role Visa ...

Role Description This is a full-time on-site role for a Machine Learning Research Scientist located in the San Francisco Bay Area. * Work directly with the founder to develop autonomous research ...

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Showing results 1-20

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:

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 Researcher

Alljoined

San Francisco, CA • On-site

$140K - $250K/yr

Full-time

Medical

Re-posted 15 days ago


Job description

About Alljoined
Alljoined is creating a future where humans are fully understood and augmented by technology. Our work solves the communication bottleneck between humans and computers by decoding thoughts from the brain, entirely non-invasively. We apply deep learning research to large scale neural datasets to decode internal thought directly. By advancing the frontier of neural decoding, we aim to unlock meaningful breakthroughs in human wellness and capability.
About the Role
We are looking for a talented Machine Learning Researcher to join our core R&D team. You will design and implement advanced machine learning models for EEG-based neural decoding, contribute to high-impact research, and help build the foundational infrastructure behind our brain-decoding systems.
You will work closely with leading experts in neural decoding and AI to push the boundaries of what is possible in brain-computer interfaces. This role sits at the intersection of ambitious research and rigorous engineering: you will explore novel modeling approaches while translating promising ideas into reliable, production-quality systems.
What You'll Work On
  • Develop, train, and refine state-of-the-art deep learning models for neural decoding, drawing on recent advances in architectures such as transformers and diffusion models.
  • Explore novel methods for modeling high-frequency, time-series EEG data alongside several adjacent data modalities.
  • Translate research insights into production-grade code that integrates seamlessly with our in-house BCI stack.
  • Collaborate with neuroscientists and machine learning engineers to build scalable, end-to-end neural-decoding systems.
  • Publish findings at leading machine learning and AI conferences, including NeurIPS, ICML, ICLR, and CVPR.
  • Contribute to open-source communities where appropriate.
You May Be a Good Fit If You Have
  • A bachelor's degree in computer science or a related field-such as artificial intelligence, computational neuroscience, mathematics, or biomedical engineering-and five to seven years of experience in machine learning research or applied machine learning engineering; or
  • A graduate degree (M.S. or Ph.D.) in computer science or a related field-such as artificial intelligence, computational neuroscience, or biomedical engineering-and at least three years of experience in machine learning research or applied machine learning engineering.
  • A track record of high-quality research, demonstrated through publications at leading machine learning conferences or in respected journals, including NeurIPS, ICML, ICLR, or CVPR.
  • Strong proficiency in Python and PyTorch, along with familiarity with modern machine learning tooling and distributed training.
  • Experience contributing to a production-quality codebase with modern code-review standards.

Candidates with a Ph.D. and/or experience working in a high-profile machine learning research lab are strongly preferred.
Areas of Relevant Expertise
We are particularly interested in candidates with experience in one or more of the following areas:
  • Multimodal representation learning: CLIP-style contrastive objectives and masked autoencoding.
  • Generative modeling: Diffusion models, transformer decoders, and latent GANs.
  • Temporal sequence modeling: State-space models, STFT-aware transformers, and RWKV.

Compensation Range
$140,000 - $250,000/year + equity
While this represents our expected range based on market data, final compensation will be determined based on your specific qualifications and may be outside this range.
Benefits
  • Options for housing support
  • Visa sponsorship
  • Health insurance