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Phd Machine Learning Jobs in Berkeley, CA (NOW HIRING)

Profluent

Machine Learning Scientist, BioML

Emeryville, CA · On-site +1

$200K - $330K/yr

PhD (or equivalent industry experience) in Computer Science, Machine Learning, Natural Language Processing, Applied Math, Computational Biology, Statistics, or a related field * Experience with ...

Workday

Machine Learning Engineer III

Pleasanton, CA

Bachelor's (Master's or PhD preferred) degree in engineering, data/computer science, physics, math or equivalent * 3+ yrs experience as a member of a data science, machine learning engineering, or ...

Superhuman

Machine Learning Engineer

San Francisco, CA · On-site

$250K - $385K/yr

MS / PhD in Computer Science. * 5+ years of industry experience as a machine learning engineer or applied research scientist. * A deep understanding of modern algorithms and approaches to ML, NLP ...

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Phd Machine Learning information

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How much do phd machine learning jobs pay per hour?

As of Aug 9, 2026, the average hourly pay for phd machine learning in Berkeley, CA is $27.94, according to ZipRecruiter salary data. Most workers in this role earn between $24.13 and $31.20 per hour, depending on experience, location, and employer.

What is a PhD in machine learning?

A PhD in Machine Learning is an advanced doctoral degree focused on developing new algorithms, theories, and applications in the field of machine learning. Graduates typically conduct original research, contribute to academic publications, and often specialize in areas like deep learning, reinforcement learning, or probabilistic modeling. This degree prepares individuals for careers in academia, industry research labs, or leadership roles in tech companies. The program usually involves coursework, comprehensive exams, and the completion of a dissertation based on novel research.

What are the key skills and qualifications needed to thrive as a PhD-level machine learning professional?

To thrive as a PhD-level Machine Learning professional, you need deep expertise in mathematics, statistics, computer science, and advanced machine learning algorithms, typically supported by a doctoral degree. Proficiency with programming languages like Python or R, machine learning frameworks such as TensorFlow or PyTorch, and experience with large-scale data systems are essential. Strong problem-solving skills, critical thinking, and effective communication set outstanding candidates apart by enabling them to tackle complex research challenges and collaborate across teams. These skills and qualities are crucial for driving innovation, publishing research, and developing impactful machine learning solutions.

What are some common challenges faced by PhD-level professionals in machine learning when transitioning from academia to industry roles?

PhD graduates in machine learning often encounter challenges such as adapting to faster-paced project timelines, aligning research with business objectives, and collaborating in multidisciplinary teams. Unlike academia, where projects can be exploratory and long-term, industry roles usually require actionable results within shorter deadlines. Additionally, communicating complex technical ideas to non-technical stakeholders and prioritizing practical solutions over theoretical novelty are key adjustments. However, these challenges also present opportunities for professional growth and broader impact.

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

AspectPhd Machine LearningData Scientist
Required CredentialsPhD in Computer Science, AI, or related fieldBachelor's or Master's in Data Science, Statistics, or related field
Work EnvironmentResearch labs, academia, R&D departmentsBusiness, tech companies, analytics teams
Industry UsageResearch-focused roles, advanced algorithm developmentData analysis, model building, business insights
Common Search/ComparisonYesYes

While both roles involve working with data and algorithms, a Phd Machine Learning typically focuses on research, developing new models, and theoretical work, often in academic or R&D settings. A Data Scientist applies these techniques to solve practical business problems, analyze data, and generate insights in industry environments.

What cities near Berkeley, CA are hiring for Phd Machine Learning jobs? Cities near Berkeley, CA with the most Phd Machine Learning job openings:
Phd Machine Learning jobs near you
Infographic showing various Phd Machine Learning job openings in Berkeley, CA as of July 2026, with employment types broken down into 1% As Needed, 72% Full Time, 25% Part Time, 1% Temporary, and 1% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $58,122 per year, or $27.9 per hour.

Machine Learning Scientist, Pretraining

Profluent

Emeryville, CA • On-site, Remote

$200K - $330K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 6 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.
The Role
We're looking for a motivated and creative Machine Learning (ML) Scientist to drive research into pretraining large-scale deep learning models for biomolecular design. 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 autoregressive, diffusion and representation learning models for protein design
  • Collaborate across the machine learning and protein design teams to apply, adapt and improve pretraining techniques from other domains to biomolecular deep learning models
  • Architect, implement, and optimize core infrastructure to support the pretraining of protein language models
  • Curate relevant datasets and design tasks for rigorous evaluation of generative models
  • 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 and pretraining large scale LLMs or other models in biomolecular domain
  • Publications at major machine learning conferences (NeurIPS, ICML, ICLR) or scientific journals (Nature, Science, Nature Biotech, Nature Methods, PNAS) or experience pre-training LLMs at frontier AI/ML labs
  • 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

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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