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Computational Biology Software Developer Jobs (NOW HIRING)

MarLabs

Computational Biology MLOps Engineer

Indianapolis, IN · On-site

$106K - $125K/yr

You bring strong software, DevOps, and data engineering fundamentals with hands on experience ... Computational Biology MLOps Engineer | Day-to-Day * Build and maintain ML infrastructure, including ...

Marlabs

Computational Biology MLOps Engineer

San Diego, CA · On-site +1

$118K - $139K/yr

You bring strong software, DevOps, and data engineering fundamentals with hands on experience ... Computational Biology MLOps Engineer | Day-to-Day * Build and maintain ML infrastructure, including ...

Onebridge

Computational Biology MLOps Engineer

San Diego, CA · On-site

$118K - $139K/yr

You bring strong software, DevOps, and data engineering fundamentals with hands on experience ... Computational Biology MLOps Engineer | Day-to-Day * Build and maintain ML infrastructure, including ...

The University Of Chicago

Develops and applies algorithms, computational methods, and software solutions to identify ... Experience using Python, Perl, or other programming languages for computational biology ...

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Computational Biology Software Developer information

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How much do computational biology software developer jobs pay per hour?

As of Sep 10, 2026, the average hourly pay for computational biology software developer in the United States is $59.26, according to ZipRecruiter salary data. Most workers in this role earn between $49.28 and $68.27 per hour, depending on experience, location, and employer.

What is a computational biology software developer?

A Computational Biology Software Developer is a professional who designs, develops, and maintains software tools and applications to analyze biological data. They work at the intersection of computer science and biology, creating algorithms and systems that help researchers interpret complex datasets, such as genomic or proteomic information. Their work is vital for advancing research in fields like genetics, drug discovery, and personalized medicine. Typically, they collaborate with scientists, bioinformaticians, and other developers to solve biological problems using computational approaches.

How does a computational biology software developer typically collaborate with biologists and data scientists on research projects?

A Computational Biology Software Developer frequently works in multidisciplinary teams, collaborating closely with biologists to understand research goals and with data scientists to process and analyze complex datasets. Developers translate biological questions into computational tasks, design bioinformatics tools, and ensure that their software meets the scientific requirements of the project. Regular communication and iterative feedback are essential, as developers often need to adapt their solutions based on experimental results or evolving project needs. This collaborative environment fosters innovation and provides exposure to diverse scientific and technical challenges.

What are the key skills and qualifications needed to thrive as a computational biology software developer, and why are they important?

To thrive as a Computational Biology Software Developer, you need strong programming skills (commonly in Python, R, or C++), a solid background in algorithms and bioinformatics, and typically a degree in computer science, bioinformatics, or a related field. Familiarity with tools such as Bioconductor, BLAST, and version control systems (like Git) is essential, along with experience using scientific computing environments. Outstanding problem-solving skills, attention to detail, and effective communication are important soft skills for collaborating with interdisciplinary teams and translating complex biological data into actionable insights. These skills ensure accurate data analysis, robust software development, and effective contribution to research and innovation in computational biology.

What is the difference between Computational Biology Software Developer vs Bioinformatics Analyst?

AspectComputational Biology Software DeveloperBioinformatics Analyst
Required CredentialsBachelor's or Master's in Bioinformatics, Computer Science, or related fieldBachelor's or Master's in Bioinformatics, Biology, or related field
Work EnvironmentDevelops software tools, algorithms, and applications for biological data analysisAnalyzes biological data, interprets results, and reports findings
Employer & Industry UsagePharmaceutical companies, biotech firms, research institutionsResearch labs, healthcare organizations, academic institutions

While both roles require a background in biology and computer science, Computational Biology Software Developers focus on creating software tools and algorithms, whereas Bioinformatics Analysts primarily interpret biological data and generate reports. Both roles are essential in the biotech and research industries, often collaborating to advance scientific discoveries.

What are popular job titles related to Computational Biology Software Developer jobs?

For Computational Biology Software Developer jobs, the most frequently searched job titles are:

Infographic showing various Computational Biology Software Developer job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 88% Full Time, 7% Part Time, and 3% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $123,262 per year, or $59.3 per hour.

Computational Biologist MLOps Engineer

San Diego, CA • On-site

Marlabs
IT Services • 1 - 5K employees
Learn more about Marlabsexternal

Other

Re-posted 18 days ago

Job description

Marlabs, a global AI and Digital Solutions Consulting firm, delivers intelligent solutions across AI, data, analytics, and product engineering. Since 2000, we have partnered with some of the largest healthcare, life sciences, financial services, and government organizations worldwide. As we continue to expand our global footprint, we have an exciting opportunity for a highly skilled Computational Biology MLOps Engineer to join our innovative and dynamic team.


This role requires onsite work three (3) days per week in Indianapolis, IN or San Diego, CA.


Computational Biology MLOps Engineer | About You

As a Computational Biology MLOps Engineer, you are responsible for building and scaling the ML infrastructure that supports next generation in silico protein design and engineering. You bridge cutting edge AI research and production systems at the intersection of machine learning, computational biology, and high performance computing. You thrive in cross functional environments and partner closely with computational scientists and platform engineers to accelerate research velocity. You bring strong software, DevOps, and data engineering fundamentals with hands on experience across CI/CD, orchestration, and distributed training. Experience working with scientific or multimodal data and interest in protein language and generative models is a plus.


Computational Biology MLOps Engineer | Day-to-Day

  • Build and maintain ML infrastructure, including CI/CD pipelines (GitHub Actions) for model training, evaluation, and deployment.
  • Orchestrate compute across Kubernetes clusters and SLURM and HPC environments to optimize utilization for large scale training.
  • Develop robust and scalable data pipelines that deliver ML ready datasets from biological sources such as PDB and mmCIF files, sequence databases, and assay readouts.
  • Create tools and frameworks that enable rapid iteration on protein language models, diffusion models, and other generative approaches.
  • Architect systems that scale across distributed environments and support multimodal datasets for large foundational models.
  • Implement monitoring, logging, and alerting to ensure reliability, performance, and cost efficiency of production ML systems.


Computational Biology MLOps Engineer | Skills & Experience

  • 5+ years of overall industry experience in software engineering, DevOps, data engineering, or ML engineering roles, including 3+ years of focused MLOps experience building and maintaining production grade ML infrastructure.
  • Proven CI/CD expertise with GitHub Actions and strong DevOps practices including infrastructure as code, version control, and collaborative workflows.
  • Hands on Kubernetes experience in deploying and managing containerized ML workloads with familiarity using container registries.
  • Proficiency with SLURM or similar job schedulers in HPC environments and experience with distributed training optimization including mixed precision and checkpointing.
  • Strong Python skills and experience with major ML frameworks including PyTorch, TensorFlow, or JAX.
  • Experience building ETL processes and scalable data and feature pipelines and experience with cloud platforms such as AWS, GCP, or Azure.
  • Preferred experience with scientific data, protein structure formats such as PDB and mmCIF, protein AI models including ESM, and agentic systems such as MCP, LangGraph, and LangChain.

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