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Machine Learning Researcher Jobs in Berkeley, CA

Alljoined

Machine Learning Researcher

San Francisco, CA · On-site

$140K - $250K/yr

About the Role We're seeking a talented Machine Learning Researcher to join our core R&D team. This role involves designing and implementing advanced machine learning models for EEG-based neural ...

MSCI

Machine Learning Researcher

San Francisco, CA · On-site

$144K - $187K/yr

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

Machine Learning Researcher

San Francisco, CA · On-site

$144K - $187K/yr

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

Machine Learning Researcher

San Francisco, CA

$144K - $187K/yr

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 ...

Kiddom

Machine Learning Researcher

San Francisco, CA

$180K - $280K/yr

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 ...

Inference

Machine Learning Researcher

San Francisco, CA · On-site

$250K - $350K/yr

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 ...

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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 May 30, 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 are the key skills and qualifications needed to thrive as a Machine Learning Researcher, and why are they important?

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 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 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

Machine Learning Researcher

Alljoined

San Francisco, CA • On-site

$140K - $250K/yr

Full-time

Medical, Retirement

Posted 24 days ago

Job description

About Alljoined
Alljoined aims to solve the communication bottleneck between humans and technology by decoding thoughts from the brain, entirely non-invasively. We apply deep learning research to large scale EEG datasets collected on affordable hardware to decode images, text, and video initially, and eventually moving to internal thought. We are state-of-the art in capabilities and are fully vertically integrated. Our goal is to develop a general consumer interface to completely transform what we can do at home and work.
We are actively growing our world-class team of researchers to build the next interface to improve individual lives as well as the well-being of society as a whole.
About the Role
We're seeking a talented Machine Learning Researcher to join our core R&D team. This role involves designing and implementing advanced machine learning models for EEG-based neural decoding, publishing high-impact research, and developing the core infrastructure for our brain decoding systems. You will work closely with leading experts in neural decoding and AI, pushing the boundaries of what's possible in brain computer interfaces.
Key Responsibilities
  • Research & Model Development:
    • Develop, train, and refine state-of-the-art deep learning models for neural decoding, building on the latest advancements in ML architectures (e.g., transformers, diffusion models, etc).
    • Explore novel approaches for modeling high-frequency timeseries EEG datasets along with a number of adjacent data modalities.
    • Translate research insights into production-grade code that integrates seamlessly with our in-house BCI stack.
  • Collaboration & Publication:
    • Collaborate with a team of neuroscientists and ML engineers to create scalable, end-to-end neural decoding solutions.
    • Publish findings at top-tier ML and AI conferences (e.g., NeurIPS, ICML, ICLR, CVPR) and contribute to open-source communities where appropriate.

Qualifications
  • Educational Background & Experience:
    • Bachelor's degree in Computer Science or a related domain (e.g., AI, Computational Neuroscience, Mathematics, Biomedical Engineering, etc), with 5-7 years of experience in ML research or applied ML engineering; OR
    • Graduate degree (M.S., Ph.D.) in Computer Science or a related domain (e.g., AI, Computational Neuroscience, Biomedical Engineering) with 3+ years of experience in ML research or applied ML engineering.
    • Candidates with a Ph.D. and/or experience in high profile ML research labs are strongly preferred.
  • Technical Expertise:
    • Multimodal Representation Learning (CLIP-style contrastive objectives, masked autoencoding)
    • Generative Modeling (diffusion, transformer-decoders, latent-GANs)
    • Temporal Sequence Modeling (state-space models, STFT-aware transformers, RWKV)
    • A track record of high-quality research demonstrated by publications in top ML conferences or journals (e.g., NeurIPS, ICML, ICLR, CVPR).
    • Strong proficiency in Python and PyTorch, familiarity with ML tooling, and distributed training.
    • Experience working in a production-quality codebase with modern code review standards.

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
  • 3% 401k matching
  • Health insurance

Apply