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Weekday Machine Learning Research Scientist Jobs in Berkeley, CA

Profluent

Machine Learning Research Engineer

Emeryville, CA · On-site +1

$237K/yr

Partner with ML and protein design scientists to prototype research ideas and bring them into ... Science, Machine Learning, or a related field * 3+ years of hands-on experience building and ...

Slope

Research Scientist

San Francisco, CA · On-site

$90 - $150/hr

About The Role As a Research Scientist here, you will develop innovative machine learning techniques and advance the research agenda of the team you work on, while also collaborating with peers ...

New

DatologyAI

Research Scientist

Redwood City, CA · On-site

$180K - $300K/yr

About the Role We're looking for a Research Scientist to investigate how intervening on training ... Some of the best researchers we've worked with have no formal training in machine learning, and ...

Skild AI

Research Scientist

San Mateo, CA

Position Overview We are looking for Research Scientists to lead the effort in developing the next ... We are looking for people with proven expertise in machine learning and/or robotics, who are ...

OpenAI

Research Scientist

San Francisco, CA · On-site

As a Research Scientist, you will develop innovative machine learning techniques and advance the research agenda while collaborating with peers across the organization. Responsibilities : • Have a ...

Advatix Inc.

Machine Learning Engineer

San Mateo, CA · On-site

$110 - $165/hr

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 ...

Collate

AI Research Scientist

San Francisco, CA · On-site

Strong background in machine learning, NLP, or related fields, with publications or equivalent ... Motivation to apply AI research in Life sciences , where rigor, safety, and impact matter deeply.

Collate

AI Research Scientist

San Francisco, CA · On-site

Strong background in machine learning, NLP, or related fields, with publications or equivalent ... Motivation to apply AI research in Life sciences , where rigor, safety, and impact matter deeply.

Collate

AI Research Scientist

San Francisco, CA · On-site

Strong background in machine learning, NLP, or related fields, with publications or equivalent ... Motivation to apply AI research in Life sciences , where rigor, safety, and impact matter deeply.

EliseAI

Senior Research Scientist

San Francisco, CA · On-site

$116K - $147K/yr

They are seeking a Senior Research Scientist to lead research initiatives in machine learning and large language models, developing predictive models and enhancing AI capabilities. Responsibilities ...

Mercor

ML Research Scientist - PhD

San Francisco, CA · Remote

$60 - $100/hr

Review complex machine learning research for alignment with domain principles and methodologies ... PhD in Machine Learning , Computer Science , AI , or a closely related field. * Published at least ...

New

EliseAI

Junior Research Scientist

San Francisco, CA · On-site

As a Junior Research Scientist, you will work with a team of researchers to develop machine ... Responsibilities : • Develop and refine machine learning architectures optimized for advanced ...

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Showing results 21-40

All JobsWeekday Machine Learning Research Scientist JobsWeekday Machine Learning Research Scientist Jobs in Berkeley, CA

Weekday Machine Learning Research Scientist information

See Berkeley, CA salary details

$61.8K

$159.3K

$213.1K

How much do weekday machine learning research scientist jobs pay per year?

As of Aug 21, 2026, the average yearly pay for weekday machine learning research scientist in Berkeley, CA is $159,320.00, according to ZipRecruiter salary data. Most workers in this role earn between $131,600.00 and $211,800.00 per year, depending on experience, location, and employer.

What does a Weekday Machine Learning Research Scientist do?

A Weekday Machine Learning Research Scientist conducts research and develops new algorithms or models in the field of machine learning, typically during standard business days (Monday to Friday). Their work involves designing experiments, analyzing data, publishing findings, and collaborating with other scientists or engineers. They may focus on improving existing machine learning techniques or creating innovative solutions for real-world problems. This role often requires a strong background in mathematics, computer science, and statistics, as well as proficiency in programming languages like Python or R.

What are some common challenges faced by a Weekday Machine Learning Research Scientist, and how are they typically addressed within the team?

Weekday Machine Learning Research Scientists often encounter challenges such as managing large datasets, tuning complex models, and keeping up with rapidly evolving research. Collaboration is key—team members regularly hold meetings to share findings, brainstorm solutions, and review code. Access to robust computational resources and mentorship from senior researchers helps address technical obstacles, while a structured, weekday schedule allows for focused research and effective work-life balance.

What are the key skills and qualifications needed to thrive as a Weekday Machine Learning Research Scientist, and why are they important?

To thrive as a Weekday Machine Learning Research Scientist, you need a solid background in mathematics, statistics, programming (Python, R), and a relevant advanced degree such as a Master's or Ph.D. in computer science or a related field. Expertise with machine learning frameworks (like TensorFlow, PyTorch), data processing tools, and familiarity with cloud computing platforms are typically required. Strong analytical thinking, problem-solving abilities, and clear communication skills help you collaborate with teams and present complex findings effectively. These skills are crucial for developing innovative models, delivering impactful research, and ensuring successful implementation in real-world applications.

What is the difference between Weekday Machine Learning Research Scientist vs Weekend Machine Learning Research Scientist?

AspectWeekday Machine Learning Research ScientistWeekend Machine Learning Research Scientist
CredentialsMaster's or PhD in Computer Science, Data Science, or related fieldsSame as weekday role
Work EnvironmentTypically in office or research labs during standard hoursFlexible hours, often part-time or project-based
Employer & Industry UsageTech companies, research institutions, startupsFreelance projects, consulting firms, academic collaborations

The main difference between a Weekday Machine Learning Research Scientist and a Weekend Machine Learning Research Scientist lies in their work schedule and environment. Weekday roles usually involve full-time employment with structured hours, while weekend roles are often part-time or freelance, offering more flexibility. Both roles require similar credentials and are used across tech and research industries.

What cities near Berkeley, CA are hiring for Weekday Machine Learning Research Scientist jobs?

Cities near Berkeley, CA with the most Weekday Machine Learning Research Scientist job openings:

Weekday Machine Learning Research Scientist jobs near you

Machine Learning Research Engineer

Profluent

Emeryville, CA • On-site, Remote

$237K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 28 days ago

Job description

Profluent is the frontier AI lab for biology. Profluent builds powerful foundation models for all of life's molecules, unlocking solutions that transform medicine, agriculture, and beyond. Founded in 2022 and headquartered in Emeryville, CA, Profluent is backed by leading investors including Altimeter Capital, Bezos Expeditions, Spark Capital, Insight Partners, Air Street Capital, AIX Ventures, and Convergent Ventures and has raised over $150M to date.
We're looking for an experienced Machine Learning Engineer to build and improve the models and ML systems that drive our protein design efforts. In this role, you'll deploy and optimize large-scale generative models for protein design, and develop the surrounding infrastructure and tooling that enable our ML and protein design scientists to work faster and more confidently. As an early member of a small, fast-moving engineering team, you'll have significant ownership over our ML stack and the opportunity to shape how our platform evolves.
Responsibilities
  • Build robust, reproducible and user-friendly pipelines for automated model fine-tuning, alignment and evaluation
  • Design and implement modular, easy-to-maintain, multi-model pipelines for protein design
  • Develop highly scalable ETL pipelines to process petabyte-scale protein data for model pretraining
  • Optimize model training and inference code to maximize throughput and resource utilization when deployed at scale
  • Develop software and infrastructure that enable the ML team to work quickly and frictionlessly in distributed and multi-cloud environments
  • Partner with ML and protein design scientists to prototype research ideas and bring them into production

Who You Are
  • You're comfortable taking ownership and working independently in a fast-moving environment
  • You're an execution-oriented engineer who maintains high standards, and focuses on the highest-impact work
  • You're comfortable owning the full stack of your work, from training code to the infrastructure it runs on
  • You care deeply about model quality, efficiency, and reliability
  • You're willing to step beyond your core responsibilities when the team needs it

Representative Projects
  • Building hyperparameter search frameworks for SFT and Alignment workflows
  • Increasing protein language model throughput during long context generation
  • Updating existing model architectures to work and run efficiently on new GPU hardware
  • Implementing a protein design pipeline that integrates prompt retrieval, sequence generation, attribute prediction, and structure prediction
  • Establishing an ETL pipeline for sampling and tokenizing training datasets from an internal database of billions of sequences
  • Developing a benchmarking and evaluation system for newly trained sequence generation models
  • Contributing to the development of an internal service that provides transparent multi-node job submission for ML scientists

Qualifications
  • BS or MS in Computer Science, Machine Learning, or a related field
  • 3+ years of hands-on experience building and training ML models in PyTorch
  • Strong Python and software engineering fundamentals, including testing, code quality, and version control
  • Experience profiling, benchmarking, and optimizing ML model training and inference
  • Experience implementing or optimizing transformer-based architectures
  • Familiarity with cloud infrastructure and containerization (GCP, AWS, Azure, Kubernetes, Docker)
  • Strong fundamentals in ML, statistics, and/or linear algebra

Preferences
  • Familiarity with protein language models or computational biology
  • Experience with GPU-level optimization (CUDA, Triton)
  • Experience with distributed training (DDP, FSDP, multi-node GPU clusters)
  • Experience with databases and data processing pipelines
  • Experience orchestrating multi-step ML workflows
  • Experience building backend systems that serve ML models in production
  • Contributions to open source ML projects or published research

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

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.
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.
Hiring Salary Range
$200,000-$330,000 USD

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