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

Ai2

Young Investigator, FlexOlmo

Berkeley, CA · On-site

$57K - $57K/yr

... machine learning, natural language processing, language and vision, or related areas. • ... We are a Seattle-based non-profit AI research institute founded in 2014 by the late Paul Allen.

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All JobsNonprofit Machine Learning JobsNonprofit Machine Learning Jobs in Berkeley, CA

Nonprofit Machine Learning information

See Berkeley, CA salary details

$31.2K

$52.1K

$107.8K

How much do nonprofit machine learning jobs pay per year?

As of Sep 6, 2026, the average yearly pay for nonprofit machine learning in Berkeley, CA is $52,141.00, according to ZipRecruiter salary data. Most workers in this role earn between $39,800.00 and $56,300.00 per year, depending on experience, location, and employer.

What is a nonprofit machine learning professional?

A Nonprofit Machine Learning professional is someone who applies machine learning and data science techniques to help nonprofit organizations achieve their missions. This can include using predictive analytics to improve fundraising, optimize program delivery, or analyze the impact of initiatives. They often work with large datasets, develop algorithms, and collaborate with program staff to find data-driven solutions to social challenges. Their work helps nonprofits make more informed decisions and maximize their impact.

How does the role of a machine learning specialist in a nonprofit differ from similar roles in the private sector?

In a nonprofit setting, a Machine Learning Specialist often works with limited resources and must prioritize projects that directly support the organization's mission, such as optimizing donor outreach, improving program delivery, or analyzing social impact. Collaboration with program staff, fundraisers, and volunteers is common, requiring strong communication skills to translate technical insights into actionable strategies. Unlike the private sector, where profitability may be the primary focus, success in a nonprofit environment is measured by social outcomes and mission alignment. This role offers the opportunity to see the tangible impact of your work and can lead to leadership or strategic roles within the organization as you demonstrate value.

What are the key skills and qualifications needed to thrive as a nonprofit machine learning specialist, and why are they important?

To thrive as a Nonprofit Machine Learning Specialist, you need a strong background in data analysis, statistics, and machine learning, typically supported by a degree in computer science or a related field. Proficiency with programming languages like Python or R, experience with machine learning frameworks (such as TensorFlow or scikit-learn), and familiarity with donor management or CRM systems are highly valuable. Strong communication, problem-solving, and collaboration skills help translate technical solutions into meaningful impact for nonprofit missions. These abilities are crucial for leveraging data-driven insights to optimize resources, drive fundraising, and advance organizational goals.

What is the difference between Nonprofit Machine Learning vs Nonprofit Data Analyst?

AspectNonprofit Machine LearningNonprofit Data Analyst
Required SkillsMachine learning algorithms, programming (Python, R), statistical modelingData visualization, statistical analysis, Excel, SQL
Work EnvironmentResearch-focused, technical teams, data science projectsReporting, data interpretation, stakeholder communication
Employer & Industry UsageTech-driven nonprofits, research institutionsCharities, advocacy groups, social service agencies

Nonprofit Machine Learning roles focus on developing predictive models and advanced algorithms, requiring programming and statistical skills. Nonprofit Data Analysts primarily interpret and visualize data to inform decisions. While both roles support nonprofit missions, Machine Learning positions are more technical and research-oriented, whereas Data Analysts focus on data reporting and communication.

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

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

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

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

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

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

Nonprofit Machine Learning jobs near you
Infographic showing various Nonprofit Machine Learning job openings in Berkeley, CA as of June 2026, with employment types broken down into 79% Full Time, and 21% Part Time. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $52,141 per year, or $25.1 per hour.

Machine Learning Researcher - Springtail

Astera

Emeryville, CA • On-site

$150K - $300K/yr

Full-time

Re-posted 14 days ago

Job description

About Astera
Astera is a private foundation on a mission to steer science and technology toward an abundant future. We believe the coming years will bring an era of unprecedented scientific and technological advancement as exponential progress in AI converges with central advances in other fields to dramatically accelerate innovation. This inflection point provides an unparalleled opportunity to fundamentally rethink the institutions, systems, and tools that drive scientific progress.
Unlike traditional non-profit research organizations, Astera funds and operates projects like high-velocity startups, allowing us to focus on ambitious goals, match structure to problem, and attract strong technical talent and leadership. You can read more about our mission, vision, and programming here.
Position Summary
Datasets in many areas, science in particular, are often small, heterogeneous, and expensive. Human scientists can take these datasets and generate models to describe them, but this process of model induction is labor-intensive and error-prone. Machine learning is a general and scalable solution, but it is not uniformly sample efficient.
The Astera Institute is seeking a Machine Learning Researcher to help surmount this barrier with new architectures for data-efficient and general model induction. This includes bootstrapped program synthesis, along with components for a system that synthesizes its own learning algorithms - a machine learning strange loop. This is a full time position that reports to Timothy Hanson.
Responsibilities
  • Hypothesize, test, and refine means of improving generalization performance of common architectural elements, including different forms of attention. This includes devising controlled datasets to elucidate e.g. learning order & learned representations.
  • Think both mathematically and empirically about problems of runtime inference in gradient-trained networks, with an eye to the extensive literature on statistical learning and an open mind to the many forms of constrained optimization.
  • Contribute to a well-documented and well-instrumented code base that is performant where necessary yet expeditious where experimental throughput demands.

Qualifications and Experience
  • Masters or equivalent in machine learning, mathematics, or equivalent fields (strong candidates from neuroscience are encouraged to apply).
  • Fluency with Pytorch, and familiarity with JAX, CUDA, and/or Triton + their open-source ecosystems.
  • Demonstrated ability do fundamental research.
  • Demonstrated ability to work in teams.

Location
This position is hybrid at our office in Emeryville, CA. Some travel may be required from time-to-time for in-person collaboration and work.
Compensation
The posted salary range is based on location in the Bay Area. The successful candidate will receive a competitive compensation package, commensurate with their experience and location.
  • Benefits summary

Apply