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Computational Protein Engineer Jobs (NOW HIRING)

Jj

Director, Protein Sciences

Cambridge, MA · On-site

  • Retirement

  • PTO

The Director, Protein Sciences will integrate target biology insight, computational protein design, cell engineering, and experimental protein sciences to drive the generation of high-quality ...

Jj

Director, Protein Sciences

Spring House, PA · On-site

  • Retirement

  • PTO

The Director, Protein Sciences will integrate target biology insight, computational protein design, cell engineering, and experimental protein sciences to drive the generation of high-quality ...

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Computational Protein Engineer information

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$48.5K

$121.5K

$137.5K

How much do computational protein engineer jobs pay per year?

As of Aug 15, 2026, the average yearly pay for computational protein engineer in the United States is $121,515.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,500.00 and $131,500.00 per year, depending on experience, location, and employer.

What is computational protein engineering?

Computational protein engineering is a field where professionals design and modify proteins using computer models and algorithms to improve their functions or create new ones. It involves techniques such as molecular modeling, bioinformatics, and machine learning to predict protein structures and behaviors, often supporting experimental research and development.

What are some common challenges faced by computational protein engineers when collaborating with experimental teams?

One common challenge computational protein engineers encounter is ensuring that their in silico predictions align with experimental feasibility and constraints. Effective communication is essential, as computational models may suggest protein designs that are difficult to express or characterize in the lab. Bridging the gap between computational outputs and experimental validation often requires iterative feedback, flexibility, and a strong collaborative relationship with wet-lab scientists. This interdisciplinary teamwork ultimately leads to more robust and successful protein engineering outcomes.

What does a computational protein engineer do?

A Computational Protein Engineer uses computer-based tools and algorithms to design, model, and optimize proteins for specific functions or applications. They simulate protein structures, predict how proteins will fold, and engineer changes to improve stability, activity, or binding properties. This work often supports advancements in drug development, biotechnology, and synthetic biology, allowing for faster and more precise engineering compared to traditional laboratory methods. Computational Protein Engineers collaborate with experimental scientists to validate their designs and drive innovation in healthcare and industry.

What is the difference between Computational Protein Engineer vs Structural Biologist?

AspectComputational Protein EngineerStructural Biologist
Required CredentialsDegree in bioinformatics, computational biology, or related fieldDegree in biochemistry, molecular biology, or related field
Work EnvironmentPrimarily computational, using software and modeling toolsLaboratory-based, using techniques like X-ray crystallography or cryo-EM
Employer & Industry UsagePharmaceutical, biotech, research institutionsAcademic, research institutions, biotech companies
Common Search & Comparison IntentUnderstanding roles in protein design and modelingUnderstanding structural analysis of proteins

While both roles focus on proteins, Computational Protein Engineers primarily use computational methods to design and analyze proteins, whereas Structural Biologists study protein structures through experimental techniques. Both are essential in protein research but differ in their approaches and tools.

What are the key skills and qualifications needed to thrive as a computational protein engineer?

To thrive as a Computational Protein Engineer, you need a strong background in biochemistry, structural biology, and computational modeling, usually supported by an advanced degree in a related field. Proficiency in molecular modeling software (such as Rosetta or PyMOL), programming languages (like Python or C++), and familiarity with bioinformatics databases is often required. Strong problem-solving skills, attention to detail, and effective communication abilities help you collaborate across interdisciplinary teams and interpret complex data. These skills are crucial for designing novel proteins, predicting their behavior, and advancing research or therapeutic applications.

How much does a computational protein engineer make?

A computational protein engineer's salary typically ranges from $80,000 to $150,000 annually, depending on experience, education, and location. Entry-level positions may start lower, while experienced professionals with specialized skills in bioinformatics and molecular modeling can earn higher salaries.
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What job categories do people searching Computational Protein Engineer jobs look for?

The top searched job categories for Computational Protein Engineer jobs are:

Computational Protein Engineer jobs near you
Infographic showing various Computational Protein Engineer job openings in the United States as of August 2026, with employment types broken down into 92% Full Time, 2% Part Time, and 6% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $121,515 per year, or $58.4 per hour.

Scientist - Protein Engineering

Merge Labs

San Francisco, CA • On-site

$120K - $215K/yr

Full-time

Re-posted 24 days ago

Job description

Merge Labs is a frontier research lab with the mission of bridging biological and artificial intelligence to maximize human ability, agency and experience. We're pursuing this goal by developingfundamentally new approaches to brain-computer interfaces that interact with the brain at high bandwidth, integrate with advanced AI, and are ultimately safe and accessible for anyone to use.
About the team:
Our Bio team designs, builds, and characterizes the biotechnologies that form the foundation of next-generation brain-computer interfaces. We combine molecular engineering, synthetic biology, neuroscience, and advanced physical methods such as ultrasound to establish less invasive, high-bandwidth connections with neurons. The Bio team develops our core molecular technologies, validates their performance in vitro and in vivo, and demonstrates their advanced capabilities in animal models. We build custom experimental setups and pipelines and collaborate closely with engineers and data scientists. We work across disciplines to come up with creative ideas and solve some of the most challenging problems in biotechnology.
About the role
As a Protein Engineer in a BCI company, you will design, build, and optimize the key biomolecules that translate between the languages of cells and machines - turning neuronal activity at the molecular scale into interpretable signals and enabling precise modulation.
You'll work with unconventional proteins - from atypical biosensors and membrane proteins to complex, multi-component assemblies - and use your biophysical insights, high-throughput experimental methods, and close collaboration with our computational team to push the boundaries of what these molecules can do. Your work will set the molecular foundation for next-generation brain-computer interfaces.
In this role, you will:
  • Design and implement diverse protein engineering strategies - from rational design and computational modeling to directed evolution and combinatorial library - to build dynamic molecular systems with desirable properties.
  • Build and characterize protein variants at high throughput to test and iterate hypotheses rapidly and rigorously: implement and optimize scalable workflows from library generation, expression in various in vitro systems, to standard and custom assays.
  • Collaborate with our computational team to establish models linking sequences and structures to function, guide the generation of future constructs, and augment our intuition.
  • Explore the mechanisms behind complex biomolecules and translate that understanding into creative, out-of-the-box designswith the support of our biochemists, structural biologists, and computational teams.
  • Develop novel screening and validation methods to further accelerate the entire design-build-iterate loop and ensure a smooth transition toward in vivo applications.

You might thrive in this role if you:
  • Have a PhD in Bioengineering, Biophysics, Biochemistry, or a related field, or have equivalent experience leading research projects end-to-end.
  • Are proficient in library construction, protein expression in mammalian cells, and standard characterization.
  • Are comfortable using computational approaches for protein engineering and understand the fundamental principles involved.
  • Think mechanistically: you are motivated by understanding how things work, not just that they work.
  • Enjoy working with dynamic, multi-state proteins and/or complex protein assemblies.
  • Feel joy in collaboration and communicate naturally with experts across disciplines.
  • Are energized by 0->1 innovations and always on the lookout for creative ways to do better.
  • Want to be part of a fast-paced team working on frontier scientific and technical problems.

Nice to have
  • Experience with engineering multi-state proteins, membrane proteins, and multi-component protein assemblies.
  • Experience with protein expression in primary neurons, brain organoids, or brain tissues.
  • Experience with large-scale screening.
  • Experience with creative assay development.
  • Familiarity with machine learning or data-driven design approaches.

If you're excited about this role but don't meet every qualification, please apply. As we build, we're hiring for complementary strengths to form a high-impact team.
For more information about hiring at Merge, please visit our Hiring FAQ
Merge Labs does not discriminate on the basis of race, color, religion, national origin, age, sex, sexual orientation, gender, gender identity, gender expression, marital status, physical or mental disability, medical condition, genetic information, family status, ancestry, citizenship, U.S. military (state and federal) and veteran status, or any other legally protected status. It is our intention that all applicants be given equal opportunity and that selection decisions are based on job related factors. We are an equal opportunity employer.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@merge.io.

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