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On Call Bioinformatics Machine Learning Jobs (NOW HIRING)

Apple

Machine Learning Engineer - Health AIML

Cupertino, CA · On-site

$212K - $318K/yr

D. in Computer Science, Machine Learning, Bioinformatics, or a related field. Strong background in generative models, natural language processing (NLP), and large language models (LLMs). 5+ years of ...

LLNL

Bioinformatics Scientist

Livermore, CA · On-site

We have an opening for a Bioinformatics Scientist to conduct research, training, and evaluating ... PhD in Computational Biology, Biophysics, Computational Bioengineering, Machine Learning ...

LLNL

Bioinformatics Scientist

Livermore, CA

We have an opening for a Bioinformatics Scientist to conduct research, training, and evaluating ... PhD in Computational Biology, Biophysics, Computational Bioengineering, Machine Learning ...

LLNL

Bioinformatics Scientist

Livermore, CA · On-site

We have an opening for a Bioinformatics Scientist to conduct research, training, and evaluating ... PhD in Computational Biology, Biophysics, Computational Bioengineering, Machine Learning ...

Cff

Scientist I, Bioinformatics

Lexington, MA

Understands well the biology application domain, proficient in bioinformatics tools, databases, software development, general and numerical algorithms, statistics and machine learning. Capable of ...

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 ...

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

As of Jun 19, 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 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 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 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.
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On Call Bioinformatics Machine Learning jobs near you

Director, Machine Learning, Virtual Cell Initiative

Arc Institute

Palo Alto, CA • On-site, Remote

$380K - $420K/yr

Full-time

Posted 23 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.
Why this position could be the best job you've ever had?
  • Work at the center of AIxBio with the potential to revolutionize drug discovery for the world.
  • Work in a unique environment that incorporates both wet lab data generation and frontier AI modelling in an active learning loop.
  • Join a new type of research org that fuses high-velocity execution of a startup with the intellectual rigor of a world-class academic institute, with a long runway to tackle some of the hardest - and highest potential - challenges in science today.
  • Collaborate with some of the most accomplished scientists and entrepreneurs in the world.

About the position
We are searching for an innovative scientific leader experienced in building predictive models based on single-cell genomic data. The chosen candidate will spearhead the development and application of advanced machine learning models tailored for perturbative gene expression modeling, in the context of Arc's virtual cell initiative.
About you
  • You are passionate about machine learning, ideally with experience or strong interest in biology and single-cell genomics.
  • You want to develop highly innovative and accurate biology-inspired multimodal machine learning models.
  • You are excited about collaborating with a multidisciplinary team of computational and experimental biologists at Arc.
  • You are a strong communicator, capable of translating complex technical concepts at the intersection of machine learning and biology.
  • You are a continuous learner.
  • You are interested in recruiting and managing your own group of scientists and engineers as well as mentoring and training for other scientists.

In this position you will
  • Lead/build a team of 6 ML research scientists and engineers augmented with undergrad/masters/PhD students to contribute to the development of a state-of-the-art foundation model and agentic framework for understanding how cells respond to perturbations.
  • Work in an active learning loop with Arc's wet lab scientists to shape the world's largest and most diverse set of single cell training data across many cell contexts.
  • Collaborate closely with other research groups to integrate genomics, functional track,and omics data more broadly beyond scRNA-seq data and Perturb-seq
  • Stay up to date on the latest in frontier ML research and pioneer new architectures and approaches.
  • The ultimate goal is to build a high utility virtual cell model for use by biologists worldwide. We publish our breakthroughs to widely accelerate scientific progress and partner with some of the biggest names in AI.
  • Commit to a collaborative and inclusive team environment, sharing expertise and mentoring others.
  • Attract the very best talent in the world to support VCI initiative goals

Requirements
  • PhD in Computational Biology, Bioinformatics, Machine Learning, or a related field.
  • Minimum of 5 years of experience working in/with machine learning, well versed in frameworks such as Pytorch, TensorFlow, JAX, etc.
  • Proven experience leading research teams in a fast paced, multi-disciplinary environment.
  • Experience with or strong interest in biology with ability to communicate and collaborate successfully with biologists and pure ML engineers.
  • Excellent communication skills, both written and verbal, with a strong track record of presentations and publications.

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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