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Nonprofit Machine Learning Jobs (NOW HIRING)

Point72 Asset Management, L.P

$175 - $275/hr

What you'll do As a Machine Learning Engineer - Applied Scientist you will play a critical role in ... Volunteer opportunities * Non-profit matching gift program * Support for employee-led affinity ...

Thorn

Senior Machine Learning Engineer

$125K - $165K/yr

We are a nonprofit whose mission of defending children from sexual exploitation and abuse is deeply ... They will directly contribute to the Machine Learning team's critical function in Thorn's mission ...

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Nonprofit Machine Learning information

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$25.5K

$42.6K

$88K

How much do nonprofit machine learning jobs pay per year?

As of Sep 6, 2026, the average yearly pay for nonprofit machine learning in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 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.

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Cities with the most Nonprofit Machine Learning job openings:

What states have the most Nonprofit Machine Learning jobs?

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What job categories do people searching Nonprofit Machine Learning jobs look for?

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Nonprofit Machine Learning jobs near you
Infographic showing various Nonprofit Machine Learning job openings in the United States as of August 2026, with employment types broken down into 5% Internship, 80% Full Time, and 15% Contract. Highlights an 75% In-person, and 25% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Director, Machine Learning, Alzheimer's Disease Initiative

Arc Institute

Palo Alto, CA • On-site

Full-time

Re-posted 6 days ago

Job description

Job Summary:
Arc Institute is an independent nonprofit research organization focused on artificial intelligence and biology, aiming to accelerate scientific progress in understanding complex diseases. The Director of Machine Learning for the Alzheimer's Disease Initiative will lead a team to develop sophisticated machine learning models to analyze neurodegeneration mechanisms and predict therapeutic interventions.
Responsibilities:
• Attract, build and lead a team of exceptional machine learning research scientists dedicated to developing foundation models for cellular systems in Alzheimer's disease
• Develop and execute on a roadmap of interpretable machine learning approaches to understand disease mechanisms, with emphasis on variational inference, causal modeling, as well as modern transformer- and diffusion-based architectures
• Work closely with experimentalists on brain organoid/spheroid cellular models as well as in vivo models, working with scRNA-seq, Perturb-seq and other datasets to unravel causal gene pathways relevant to Alzheimer’s disease
• Develop predictive modeling approaches to identify how perturbations can move cell states from high risk Alzheimer’s profiles back to healthy / low risk states
• Collaborate closely with experimental biologists to ensure ML models are grounded in disease biology and can feedback into future experimental strategies
• Foster collaborations with external partners in the computational biology and neuroscience communities
• Publish high-impact research through preprints, journal publications, open source code, and presentations at leading conferences
Qualifications:
Required:
• PhD in Computational Biology, Bioinformatics, Machine Learning, Computer Science, or related quantitative field
• 7+ years of relevant experience with a minimum of 3 years of people management experience
• Strong research background with experience in academic settings (university, research institute) and/or biotech/pharmaceutical industry with a focus on scientific innovation
• Proven expertise in machine learning applications to biological datasets, with specific experience in single-cell profiling data and foundation model development
• Deep experience with interpretable machine learning approaches for biological systems (e.g. variational inference methods)
• Advanced technical skills in machine learning frameworks, particularly PyTorch, and ideally experience with model training at scale
• Publications in top-tier journals in computational biology and machine learning
• Excellent communication skills with ability to present complex machine learning concepts to both computational and biological audiences
• Proven ability to remain technically hands-on while providing effective team leadership, mentorship, and management
Preferred:
• Background in neurodegeneration research including familiarity with Alzheimer's disease datasets, pathways, networks, disease mechanisms, and eQTL analysis is a plus
Company:
Arc Institute is a biomedical science and research technology company. Founded in 2021, the company is headquartered in Palo Alto, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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