ZipRecruiter

Log In

1

On Call Bioinformatics Machine Learning Jobs (NOW HIRING)

LLNL

Machine Learning (ML) Bioengineer

Livermore, CA · On-site

As a member of our multidisciplinary team, you will collaborate with experts in machine learning, molecular simulation, optimization, and bioinformatics, and interface with experimentalists ...

LLNL

Machine Learning (ML) Bioengineer

Livermore, CA · On-site

As a member of our multidisciplinary team, you will collaborate with experts in machine learning, molecular simulation, optimization, and bioinformatics, and interface with experimentalists ...

LLNL

Machine Learning (ML) Bioengineer

Livermore, CA · On-site

As a member of our multidisciplinary team, you will collaborate with experts in machine learning, molecular simulation, optimization, and bioinformatics, and interface with experimentalists ...

next page

Showing results 1-20

People also search for

All JobsOn Call Bioinformatics Machine Learning Jobs

On Call Bioinformatics Machine Learning information

See salary details

$9

$31

$52

How much do on call bioinformatics machine learning jobs pay per hour?

As of May 30, 2026, the average hourly pay for on call bioinformatics machine learning in the United States is $31.25, according to ZipRecruiter salary data. Most workers in this role earn between $12.02 and $50.48 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an On Call Bioinformatics Machine Learning specialist, and why are they important?

To thrive as an On Call Bioinformatics Machine Learning specialist, you need a strong background in computational biology, statistics, and machine learning, often supported by an advanced degree in bioinformatics, computer science, or a related field. Familiarity with programming languages such as Python or R, experience using bioinformatics databases, and knowledge of cloud computing platforms are typically required, along with relevant certifications in data science or machine learning. Strong problem-solving abilities, attention to detail, and effective communication are crucial soft skills for collaborating with interdisciplinary teams and responding quickly to urgent issues. These skills are important for delivering rapid, accurate analyses and solutions in a dynamic and complex research environment.

What are the typical responsibilities and collaboration expectations for an On Call Bioinformatics Machine Learning professional?

As an On Call Bioinformatics Machine Learning specialist, you can expect to handle urgent data analyses, troubleshoot computational pipelines, and provide rapid support for ongoing research projects. You will frequently collaborate with biologists, data scientists, and IT teams to ensure that machine learning models are running smoothly and producing reliable results. Flexibility is key, as you may be called upon to resolve issues outside standard hours or to quickly adapt to shifting project priorities. This role also offers opportunities to contribute to process improvements and gain exposure to cutting-edge bioinformatics tools.

What is an On Call Bioinformatics Machine Learning professional?

An On Call Bioinformatics Machine Learning professional is someone who provides expertise in applying machine learning techniques to biological and biomedical data, often on an as-needed or emergency basis. They analyze complex biological datasets, such as genomics or proteomics information, to extract meaningful insights using advanced computational methods. Typically, these professionals may be brought in to troubleshoot, optimize pipelines, or solve urgent data analysis challenges when internal teams need immediate support.
More about On Call Bioinformatics Machine Learning jobs
What cities are hiring for On Call Bioinformatics Machine Learning jobs? Cities with the most On Call Bioinformatics Machine Learning job openings:
What are the most commonly searched types of Bioinformatics Machine Learning jobs? The most popular types of Bioinformatics Machine Learning jobs are:
What job categories do people searching On Call Bioinformatics Machine Learning jobs look for? The top searched job categories for On Call Bioinformatics Machine Learning jobs are:
On Call Bioinformatics Machine Learning jobs near you
Infographic showing various On Call Bioinformatics Machine Learning job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, 11% Full Time, 85% Part Time, and 3% Contract. Highlights an 69% Physical, and 31% Hybrid job distribution, with an average salary of $64,999 per year, or $31.2 per hour.

Director, Machine Learning, Alzheimer's Disease Initiative

Arc Institute

Palo Alto, CA • On-site

Full-time

Posted 19 days ago

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.

Apply