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Remote Protein Engineering Scientist Jobs (NOW HIRING)

Profluent

Research Intern, Computational

Emeryville, CA · On-site +1

$1K/wk

This is a rare opportunity to tackle open-ended scientific and engineering challenges with direct potential for high-impact publications and real-world applications in synthetic biology and protein ...

Profluent

Machine Learning Scientist, BioML

Emeryville, CA · On-site +1

$200K - $330K/yr

... protein engineering. You should be a self-directed researcher who has the ability to rapidly ... PhD (or equivalent industry experience) in Computer Science, Machine Learning, Natural Language ...

Synopsys

R&D Engineering, Scientist - 17200

Boxborough, MA · On-site +1

$212K - $318K/yr

General Information Job Title R&D Engineering, Scientist - 17200 Job ID 17200 City Boxborough State ... US-wide (remote or hybrid), with a preference for on-site collaboration You Are: You are a ...

Naval Sea Systems Command

ENGINEER/SCIENTIST

Dahlgren, VA · On-site +1

$70K - $158K/yr

You will conduct research, development and analysis of engineering data, extracting and compiling ... remote or isolated sites. You must be able to travel on military and commercial aircraft for ...

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$40.5K

$98.8K

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How much do remote protein engineering scientist jobs pay per year?

As of Jun 8, 2026, the average yearly pay for remote protein engineering scientist in the United States is $98,759.00, according to ZipRecruiter salary data. Most workers in this role earn between $78,000.00 and $116,000.00 per year, depending on experience, location, and employer.

What are some common challenges faced by Remote Protein Engineering Scientists, and how can they be addressed?

Remote Protein Engineering Scientists often encounter challenges related to effective collaboration and communication with multidisciplinary teams, since much of the work involves sharing data and coordinating experiments virtually. Managing complex computational tools and ensuring secure data sharing also require robust digital infrastructure. To address these challenges, it's important to establish clear communication protocols, utilize collaborative platforms for data analysis, and schedule regular virtual meetings to align on project goals. Building strong partnerships with lab-based colleagues and staying updated on the latest remote lab technologies can further enhance productivity and integration within the team.

What does a Remote Protein Engineering Scientist do?

A Remote Protein Engineering Scientist designs and modifies proteins using computational and experimental methods, often from a home or off-site location. They leverage bioinformatics tools, molecular modeling, and laboratory data to develop proteins with improved or novel functions for applications in biotechnology, medicine, or industry. Collaboration with multidisciplinary teams and effective communication are essential, as much of the work is coordinated virtually. Their work can involve tasks such as enzyme optimization, antibody engineering, or developing therapeutic proteins.

What are the key skills and qualifications needed to thrive as a Remote Protein Engineering Scientist, and why are they important?

To thrive as a Remote Protein Engineering Scientist, you need a strong background in molecular biology, protein chemistry, and bioinformatics, typically supported by a PhD or relevant advanced degree. Familiarity with computational modeling tools (such as Rosetta or PyMOL), high-throughput screening systems, and programming languages like Python or R is crucial. Excellent problem-solving abilities, communication skills, and the capability to collaborate virtually with cross-functional teams help set top candidates apart. These skills and qualities are vital for efficiently designing, analyzing, and optimizing proteins while contributing effectively in a remote, research-driven environment.
More about Remote Protein Engineering Scientist jobs
What cities are hiring for Remote Protein Engineering Scientist jobs? Cities with the most Remote Protein Engineering Scientist job openings:
What are the most commonly searched types of Protein Engineering Scientist jobs? The most popular types of Protein Engineering Scientist jobs are:
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Remote Protein Engineering Scientist jobs near you
Infographic showing various Remote Protein Engineering Scientist job openings in the United States as of May 2026, with employment types broken down into 3% Locum Tenens, 32% Full Time, 5% Part Time, 5% Temporary, and 55% Contract. Highlights an 91% Physical, 3% Hybrid, and 6% Remote job distribution, with an average salary of $98,759 per year, or $47.5 per hour.

Protein Design Scientist, Agentic Workflows

Profluent

Emeryville, CA • On-site, Remote

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 13 days ago

Job description

Profluent is an AI-first protein design company. Founded in 2022, we develop deep generative models to design and validate novel, functional proteins to revolutionize biomedicine. Based in Emeryville, CA, we are backed by leading investors including Altimeter Capital, Bezos Expeditions, Spark Capital, Insight Partners, Air Street Capital, AIX Ventures, and Convergent Ventures, and have raised over $150M to date.
We're looking for a Protein Design Scientist to own the development and deployment of agentic workflows for protein design. In this role, you will build systems that orchestrate protein language models, structure predictors, fitness scoring tools, and experimental feedback into automated or semi-automated design pipelines - closing the loop between computation and the wet lab.
This is a hands-on, high-ownership role. You'll work across the full stack of a design workflow: selecting and integrating models, defining agent logic and iteration strategies, building robust infrastructure for deployment, and collaborating closely with ML scientists, protein design scientists, and biologists to ensure your systems produce experimentally actionable results.
As an early employee, you will shape how Profluent approaches workflow automation and help define best practices for agentic systems in protein engineering.
Responsibilities
  • Design, build, and deploy end-to-end agentic workflows that take protein function specifications and produce ranked candidate sequences for experimental validation
  • Integrate protein language models, structure prediction tools, and scoring functions into multi-step pipelines with iteration, feedback loops, and human-in-the-loop checkpoints
  • Own the full lifecycle of workflow systems: architecture, implementation, testing, deployment, monitoring, and iteration based on experimental outcomes
  • Collaborate with ML scientists to evaluate and integrate new models into workflows, and with protein design scientists and biologists to translate scientific goals into computational specifications and ensure workflows align with experimental realities
  • Develop tooling for experiment tracking, logging, reproducibility, and versioning of design campaigns
  • Evaluate and benchmark workflow performance against experimental results, using outcomes to improve agent strategies and model selection
  • Partner with ML scientists to identify where existing models fall short in agentic contexts and inform priorities for model development, fine-tuning, and evaluation

Qualifications
  • PhD (or equivalent industry experience) in Computational Biology, Bioinformatics, Computer Science, Machine Learning, Biochemistry, or a related field
  • Minimum of 3+ years of experience as a protein design scientist
  • Strong software engineering skills: you write clean, modular, production-quality code (Python required; experience with workflow orchestration frameworks is a plus)
  • Hands-on experience with protein language models (e.g., ESM, ProGen, ProtTrans) for sequence generation, scoring, or representation
  • Demonstrated understanding of protein engineering principles: structure-function relationships, fitness landscapes, and how computational predictions connect to wet-lab validation
  • Experience building multi-component systems that chain model inference with data processing, filtering, and decision logic

Preferences (but not required)
  • Experience with agentic AI systems, LLM tool-use patterns, or multi-step reasoning pipelines
  • Familiarity with structure prediction tools (AlphaFold, RoseTTAFold, ESMFold) and inverse folding methods (ProteinMPNN, LigandMPNN)
  • Track record of computational designs that were experimentally validated
  • Experience with cloud compute platforms (GCP, AWS, Azure) and containerized deployment (Docker, Kubernetes)
  • Publications in protein design, protein engineering, or ML for biology at major conferences or journals
  • Familiarity with directed evolution, rational design, or de novo protein design strategies

What We Offer
  • High-growth opportunity with meaningful impact on the future of protein design
  • Competitive compensation package with equity participation
  • 401(k) with a strong employer match
  • Comprehensive benefits including health/dental/vision insurance
  • Generous PTO policy and commitment to work-life balance
  • Professional development opportunities in a cutting-edge field at the intersection of AI and biology

Profluent Bio, Inc is an equal opportunity employer promoting diversity and inclusion in the workspace. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical conditions, veteran status, sexual orientation, gender (including gender identity and gender expression), sex (which includes pregnancy, childbirth, and breastfeeding), genetic information, taking or requesting statutorily protected leave, or any other basis protected by law.
Employment Eligibility Verification
Legal authorization to work in the United States is required. In compliance with federal law, all persons hired must verify their identity and work eligibility and complete the required employment verification form upon hire.
Hiring Salary Range
$180,000-$250,000 USD

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