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Machine Learning Biology Jobs (NOW HIRING)

Nanite Inc.

Machine Learning Engineer

Boston, MA · On-site

Nanite is a disruptive Machine Learning/AI therapeutics company focused on revolutionizing drug ... Collaborate with chemistry and biology research teams to design data pipelines, analyze ...

Nanite Inc.

Machine Learning Engineer

Boston, MA

Nanite is a disruptive Machine Learning/AI therapeutics company focused on revolutionizing drug ... Collaborate with chemistry and biology research teams to design data pipelines, analyze ...

Leash Bio

Machine Learning Engineer

Salt Lake City, UT · On-site

$150K - $200K/yr

Machine Learning Engineer At Leash Biosciences, we are at the cutting edge of integrating machine ... While you will be dealing with massive amounts of chemical and biological information, biology and ...

LLNL

Machine Learning (ML) Bioengineer

Livermore, CA · On-site

Master's degree in Machine Learning, Computational Biology, Statistics, Computer Science, Mathematics, or a related field, or the equivalent combination of education and related experience.

LLNL

Machine Learning (ML) Bioengineer

Livermore, CA · On-site

Master's degree in Machine Learning, Computational Biology, Statistics, Computer Science, Mathematics, or a related field, or the equivalent combination of education and related experience.

Profluent

Machine Learning Scientist, BioML

Emeryville, CA · On-site +1

$200K - $330K/yr

We're looking for a motivated and creative Machine Learning (ML) Scientist to drive research into models at the intersection of complex protein biology and AI. This position offers an opportunity to ...

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Machine Learning Biology information

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$23K

$52.2K

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How much do machine learning biology jobs pay per year?

As of Jun 21, 2026, the average yearly pay for machine learning biology in the United States is $52,190.00, according to ZipRecruiter salary data. Most workers in this role earn between $44,000.00 and $60,500.00 per year, depending on experience, location, and employer.

What are some common challenges faced by professionals working in Machine Learning Biology?

Professionals in Machine Learning Biology often deal with challenges such as handling large and complex biological datasets, integrating heterogeneous data types (like genomics, proteomics, or imaging), and addressing the noise and variability inherent in biological data. Interpreting results in a biologically meaningful way and ensuring reproducibility of models can also be complex, requiring close collaboration with experimental scientists. Many teams are cross-functional, so frequent communication with biologists, clinicians, and software engineers is important for project success. While these challenges can be demanding, they also offer opportunities for innovation and significant contributions to scientific discovery or medical advances.

What is a Machine Learning Biology job?

A Machine Learning Biology job involves applying machine learning techniques to analyze biological data, such as genomic sequences, protein structures, or medical images. Professionals in this field develop algorithms to identify patterns, make predictions, and derive insights that can advance research in drug discovery, personalized medicine, and biotechnology. These roles typically require expertise in biology, data science, and programming, often using tools like Python, TensorFlow, or scikit-learn.

What are the key skills and qualifications needed to thrive in the Machine Learning Biology position, and why are they important?

To thrive as a Machine Learning Biology professional, you need expertise in both computational methods (especially machine learning and data science) and a solid understanding of biological sciences, typically supported by an advanced degree in bioinformatics, computational biology, or a related field. Familiarity with programming languages like Python or R, experience using machine learning frameworks (such as TensorFlow or scikit-learn), and working with biological databases are highly valued. Strong analytical thinking, problem-solving abilities, and effective interdisciplinary communication are key soft skills for this position. These competencies are vital for translating complex biological data into actionable insights and advancing research or product development in biotechnology and life sciences.

More about Machine Learning Biology jobs
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Machine Learning Biology jobs near you

Machine Learning Engineer

Nanite Inc.

Boston, MA • On-site

Full-time

Posted 13 days ago

Job description

Our mission is to deliver the undeliverable.
Nanite is a disruptive Machine Learning/AI therapeutics company focused on revolutionizing drug delivery. The research intern will be in a fast-paced start-up environment playing a crucial technical role in generating cell culture and transfection data. The candidate will work with senior leadership and partner projects gaining broad internal and external exposure.
Essential Functions and Duties
  • Design and implement complex data engineering processes to support innovative data science modeling
  • Collaborate with chemistry and biology research teams to design data pipelines, analyze experimental data and implement experimentally actionable feed-back loops
  • Apply and deploy established and novel statistical and machine learning algorithms to explore, understand and optimize properties of the vast delivery vehicle space, both in silico and experimentally
  • Develop robust, scalable workflows and maintain security controls to protect sensitive data across cloud and on-premise environments
  • Coordinate with cross-functional teams to deploy models and communicate results and with a focus on computational efficiency, performance, and usability
  • Design of repositories, CI/CD pipelines and integration tests for ML workflows

Qualifications
MS in Computer Science, Data Science, Statistics, Computational Biology, Computational Chemistry, or a related discipline with 2 years hands-on machine learning experience.
Knowledge, Skills, and Abilities
  • Track record developing statistical and machine learning models for complex and unconventional real-life problems
  • Strong mathematical and coding skills
  • Proficiency in Python, MLOps (W&B, MLFlow) and ML packages (scikit-learn, PyTorch, JAX), along with SQL and AWS.
  • Familiarity with ML workflow best practices.
  • Interest in applications of machine learning in biotechnology
  • Strong communication skills, both written and verbal
  • Experience doing research and working with interdisciplinary teams

Additional Preferred Experience (desired, but not essential):
  • Experience in an industry setting related to biotechnology, chemicals, or materials manufacturing
  • Experience with cheminformatics, computational chemistry, computational biology databases, data structures, material science and modelling package

Computer and modeling work required, this is an on-site position based in the Seaport of Boston, MA.

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