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Entry Level Protein Engineering Scientist Jobs (NOW HIRING)

3 Key Consulting

Seeking a highly motivated Associate Scientist to join the Protein Chemistry Engineering team (PE) at our client's state-of-the-art research facility. PE is a multidisciplinary team with broad ...

Aequor

Associate Scientist

Thousand Oaks, CA

Protein Therapeutics (PT) group is seeking a highly motivated Associate Scientist to join the ... PT is a multidisciplinary team with broad capabilities in protein engineering, expression ...

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Entry Level Protein Engineering Scientist information

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$40.5K

$98.8K

$156.5K

How much do entry level protein engineering scientist jobs pay per year?

As of Jun 7, 2026, the average yearly pay for entry level 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 the key skills and qualifications needed to thrive as an Entry Level Protein Engineering Scientist, and why are they important?

To thrive as an Entry Level Protein Engineering Scientist, you need a solid background in molecular biology, biochemistry, and protein engineering, typically supported by a relevant bachelor’s or master’s degree. Proficiency in laboratory techniques such as PCR, mutagenesis, chromatography, and familiarity with bioinformatics tools and software like PyMOL or BLAST is important. Attention to detail, strong analytical thinking, and effective teamwork enable you to excel in experimental design and data interpretation. These skills are crucial for advancing research goals, ensuring accurate results, and contributing to collaborative scientific projects.

What does an Entry Level Protein Engineering Scientist do?

An Entry Level Protein Engineering Scientist assists in the design, modification, and analysis of proteins to improve their properties for specific applications, such as drug development or industrial processes. They typically work in laboratories, conducting experiments, analyzing data, and collaborating with senior scientists to optimize protein function. Responsibilities may include molecular cloning, protein expression and purification, and using computational tools for protein modeling. This role often serves as a starting point for a career in biotechnology or pharmaceutical research, providing hands-on experience with advanced laboratory techniques and scientific problem-solving.

What are some typical challenges faced by entry-level protein engineering scientists when starting in the field?

Entry-level protein engineering scientists often encounter challenges such as adapting to complex laboratory protocols, mastering advanced analytical techniques, and interpreting experimental data accurately. Collaborating effectively within multidisciplinary teams and efficiently documenting research findings are also common hurdles. However, these challenges present valuable learning opportunities and, with mentorship and regular feedback, new scientists quickly build confidence and expertise.
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Entry Level Protein Engineering Scientist jobs near you
Infographic showing various Entry Level Protein Engineering Scientist job openings in the United States as of May 2026, with employment types broken down into 85% Full Time, 11% Part Time, and 4% Temporary. Highlights an 96% In-person, and 4% Remote job distribution, with an average salary of $98,759 per year, or $47.5 per hour.

Graduate Intern - Deep Learning in Protein Design

Manus

Waltham, MA

Full-time, Internship

Posted 2 days ago

Job description

Graduate Intern for Deep Learning in Protein Design Boston, Massachusetts, United States, Full-Time

Position Summary

Manus works across industries and value chains to accelerate the transition to BioAlternatives – better performing and more sustainable versions of complex molecules traditionally sourced from plants, animals, or fossil fuels. Our platform is proven to work across scales, bridging the Valley of Death between lab and manufacturing more efficiently and more reliably to deliver the benefits of synthetic biology today.

We are seeking a Graduate Intern in Deep Learning for Protein Design to investigate key gaps in AI-guided protein engineering and explore novel approaches to address them. The ideal candidate has experience applying deep learning methods to biological problems, such as protein sequence design, structure prediction, or mutation effect modeling. This internship offers the opportunity to work at the intersection of machine learning and synthetic biology, contributing directly to scalable, real-world applications.

Why work at Manus:

  • Opportunity – For motivated, results-oriented team members, our growth creates opportunities for personal and professional advancement.
  • Accountability – You are given the resources you need to succeed and the freedom to make it happen; in return, we hold each other accountable for our high expectations.
  • Passion – We love what we do and enjoy working with others who feel the same way. We embrace the challenge and hard work that comes with working on the cutting edge.

Key Responsibilities:

  • Evaluating state-of-the-art deep learning models for mutation effect prediction and identify their limitations (eg. Epistasis, protein dynamics, etc)
  • Drive exploratory research into potential avenues to fill gaps in DL-based approaches
  • Communicate results and insights to multidisciplinary teams, including presentations and written reports

Required Qualifications

  • Currently enrolled in a Masters or PhD program in Computer Science or BioEngineering or similar programs with emphasis on AI applications in Biological systems
  • Demonstrated experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and libraries.
  • Proficiency in programming languages such as Python and familiarity with AI-assisted coding tools (eg., Claude Code, Codex)
  • Excellent verbal and written communication skills

Preferred Qualifications

  • Familiarity with protein engineering (eg. Directed evolution, ML/AI-led)
  • Familiarity with protein language models and similar transformer-based models
  • Familiarity with benchmarking techniques and public datasets for protein sequence to function relationship
  • Experience in industrial biotechnology or a related industry

Preferred Working Style

  • Must be very well-organized and be able to handle multiple projects simultaneously.
  • Must be a quick learner who is self-motivated and able to ask questions and seek clarity.
  • Must be flexible with day-to-day duties and able to thrive in a start-up environment.
  • Must be an excellent team member with strong communication skills and a desire to work collaboratively.
  • Must hold themselves to the highest professional, scientific and ethical standards.