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Tennant Company

Machine Learning Engineer

Golden Valley, MN · On-site

$119K - $122K/yr

Tennant Company seeks a full-time Machine Learning Engineer based in Golden Valley, MN. Responsible ... off, and voluntary benefits! Total Compensation = Pay range + Benefits Posted salary ranges are ...

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Tennant Company

Machine Learning Engineer

Golden Valley, MN · Hybrid

$119K - $122K/yr

Tennant Company seeks a full-time Machine Learning Engineer based in Golden Valley, MN. Responsible ... off, and voluntary benefits! Total Compensation = Pay range + Benefits Posted salary ranges are ...

New

Tennant Company

Machine Learning Engineer

Golden Valley, MN · Hybrid

$119K - $122K/yr

Tennant Company seeks a full-time Machine Learning Engineer based in Golden Valley, MN. Responsible ... off, and voluntary benefits! Total Compensation = Pay range + Benefits Posted salary ranges are ...

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Yum

Machine Learning Engineer II

Plano, TX · On-site

As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting ... for volunteer time each calendar year. To learn more about working at Yum! -Click here. At Yum ...

System One

Machine Learning/AI Engineer

Merrifield, VA · Remote

Machine Learning/AI Engineer Location: Hybrid in Vienna, VA or Remote Pay Rate: Open to Both W2 and ... voluntary plans, as well as participation in a 401(k) plan. System One is an Equal Opportunity ...

System One

Machine Learning/AI Engineer

Merrifield, VA · Remote

Machine Learning/AI Engineer Location: Hybrid in Vienna, VA or Remote Pay Rate: Open to Both W2 and ... voluntary plans, as well as participation in a 401(k) plan. System One is an Equal Opportunity ...

System One

Machine Learning/AI Engineer

Merrifield, VA · Remote

Machine Learning/AI Engineer Location: Hybrid in Vienna, VA or Remote Pay Rate: Open to Both W2 and ... voluntary plans, as well as participation in a 401(k) plan. System One is an Equal Opportunity ...

Jobs for Humanity

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San Jose, CA · On-site

$136K - $280K/yr

Tiktok Machine Learning Engineer (Search) - E-commerce - San JoseSan JoseRegularR DJob ID: A162279 ... As well as Dental, Vision, Short/Long Term Disability, Basic Life, Voluntary Life and AD&D ...

Yum! Brands

Machine Learning Engineer II

Plano, TX

As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting ... for volunteer time each calendar year. To learn more about working at Yum! -Click here. At Yum ...

Reddit

Machine Learning Engineer

San Francisco, CA · On-site +1

$187K - $260K/yr

Design, build, and deploy industrial-level machine learning models to solve critical problems in ad ... Flexible Vacation & Paid Volunteer Time Off * Generous Paid Parental Leave Submit a resume with ...

Yum Brands

Machine Learning Engineer II

Plano, TX

As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting ... for volunteer time each calendar year. To learn more about working at Yum! -Click here. At Yum ...

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As of Jul 12, 2026, the average hourly pay for volunteer machine learning neuroscience in the United States is $28.31, according to ZipRecruiter salary data. Most workers in this role earn between $21.15 and $30.53 per hour, depending on experience, location, and employer.
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Director, Machine Learning, Alzheimer's Disease Initiative

Director, Machine Learning, Alzheimer's Disease Initiative

Arc Institute

Palo Alto, CA • On-site

Full-time

Re-posted yesterday

Job description

About Arc Institute
Arc Institute is an independent nonprofit research organization at the interface of artificial intelligence and biology, working to accelerate scientific progress and understand the root causes of complex diseases. Founded in 2021 and based in Palo Alto, Arc partners with Stanford University, UC Berkeley, and UC San Francisco.
Unlike academia, our scientists have long-term funding and industry-like resources. Unlike industry, they're free to pursue high-risk, long-term research without commercial pressures. Arc's Technology Centers and Core Investigator labs work side by side, integrating experimental and computational biology under one roof to tackle problems neither could solve alone.
Our two Institute Initiatives reflect this model in action:
  • Virtual Cell Initiative: Building a full-stack virtual cell model to identify disease mechanisms and nominate drug targets, accelerating the path from biological insight to clinical trials.
  • Alzheimer's Disease Initiative: Mapping the genes, pathways, and environmental factors behind Alzheimer's disease to develop drug candidates that address root causes.

More than 300 Arconauts work together at our Palo Alto headquarters, backed by substantial long-term philanthropic funding.
About the Position
We are searching for an exceptional scientific leader to establish a new team within Arc Institute's Computational Technology Center, serving as the Director, Machine Learning for our Alzheimer's Disease Initiative (ADI).
This ambitious initiative spans Arc's Technology Centers and Core Investigator Laboratories and focuses on high-throughput interrogation of neurodegeneration and Alzheimer's disease mechanisms using advanced gene editing and functional genomics approaches. As the Machine Learning Research Lead, ADI, you will spearhead development of sophisticated machine learning foundation models to capture cell states and infer gene regulatory networks and causal relationships to predict therapeutic interventions.
This position offers the rare opportunity to build and lead a world-class team while making direct contributions to understanding and potentially treating Alzheimer's disease through state-of-the-art computational biology and machine learning approaches.
About You
  • You are passionate about machine learning and computational biology, with expertise in applying cutting edge ML approaches to biological systems
  • You excel at developing interpretable machine learning approaches, such as variational inference and causal modeling methods
  • You are excited about building and leading a technical team while remaining hands-on with foundation model development and implementation.
  • You thrive in collaborative, multidisciplinary environments and enjoy working with both computational scientists and wet lab biologists
  • You are a continuous learner who stays current with the latest developments, in both machine learning and neuroscience
In This Position, You Will
  • 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
Required Qualifications
  • 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
  • Background in neurodegeneration research including familiarity with Alzheimer's disease datasets, pathways, networks, disease mechanisms, and eQTL analysis is a plus

The base salary range for this position is $380,000-$420,000. These amounts reflect the range of base salary that the Institute reasonably would expect to pay a new hire or internal candidate for this position. The actual base compensation paid to any individual for this position may vary depending on factors such as experience, market conditions, education/training, skill level, and whether the compensation is internally equitable, and does not include bonuses, commissions, differential pay, other forms of compensation, or benefits. This position is also eligible to receive an annual discretionary bonus, with the amount dependent on individual and institute performance factors.

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