Senior Scientist, Protein Engineering

Arbor Biotechnologies•Cambridge, MA

3d•$135,000 - $150,000

About The Position

We are seeking a Senior Scientist to drive key protein engineering workstreams within campaigns for our cutting-edge genome editing tools toward generating best-in-class molecules. You will play a key role in designing and executing protein engineering experiments, including selecting protein mutants and variants, testing in cellular and biochemical screens, analyzing downstream data, and communicating results within the team and cross-functionally. You will work closely with project leads, computational scientists, and experimental teams to apply structure-guided and AI-enabled design approaches, interpret results, and recommend next steps for assigned engineering efforts. You will also help coordinate technology hand-offs by documenting findings, summarizing technical outcomes, and communicating key learnings to internal stakeholders. This role is ideal for a rigorous and innovative molecular engineer who is comfortable combining hands-on experimentation with data analysis, structural insight, and collaborative problem-solving to help generate improved gene editors.

Requirements

PhD in biology, biochemistry, molecular biology, bioengineering, or a related discipline with a minimum of 2+ years of related experience.
3+ years of experience working with nucleic acid binding proteins, such as CRISPR nucleases, polymerases, recombinases, transcription factors, or related systems.
2+ years of experience engineering enzymes or proteins to improve function, including kinetics, stability, activity, specificity, expression, delivery, or related properties.
Expertise in evaluating sequence-structure-function relationships.
Hands-on experience with molecular biology, biochemical, or cellular approaches for measuring protein, enzyme, or editing activity.
Experience independently designing, executing, and interpreting complex experiments in protein engineering, enzymology, molecular biology, or protein biochemistry.
Ability to analyze experimental data and translate findings into clear technical recommendations.
Experience contributing to protein engineering strategy or experimental planning, with evidence of successful execution and impact.
Experience collaborating with computational scientists, project leads, or cross-functional research teams is preferred.

Nice To Haves

Hands-on experience with AAV production and testing, or mRNA generation and testing, in cellular contexts is a plus.
Experience using AI design tools for protein engineering is a plus.
Experience with CRISPR gene editing technologies is a plus.
Familiarity with Illumina sequencing workflows is a plus.

Responsibilities

Drive defined workstreams within protein engineering campaigns, including the design, generation, and evaluation of protein mutants and variants.
Recommend experimental approaches, controls, and follow-up studies in collaboration with project leads and cross-functional partners.
Select and apply protein engineering strategies, such as rational design, structure-guided engineering, deep mutational scanning, or related approaches, based on project goals and the enzyme properties being optimized.
Independently design and execute experiments to test protein engineering hypotheses and evaluate variant performance.
Analyze experimental results and recommend next experimental steps to support iterative design-build-test-learn cycles.
Apply structure-guided protein engineering approaches using experimental structures, homology models, AI-predicted structures, and other relevant models to generate and prioritize variant hypotheses.
Use protein structure visualization and molecular modeling tools, such as PyMOL, ChimeraX, and AlphaFold-derived models, to analyze active sites, protein-protein interfaces, conformational states, and sequence-structure-function relationships.
Evaluate sequence-structure-function relationships to inform protein design and interpretation of variant performance.
Design and perform biochemical assays to investigate protein properties in support of engineering goals, including activity, stability, specificity, kinetics, or other relevant functional readouts.
Interpret biochemical and cellular assay results to support protein engineering decisions and identify follow-up experiments.
Develop, optimize, and execute cell-based screening workflows using transient transfection, nucleofection, transduction, and other relevant approaches in dividing and non-dividing cell models.
Build or improve high-throughput screening strategies to increase experimental throughput, data quality, or breadth of information collected about engineered enzymes.
Design, order, and generate reagents, including AAVs, mRNA, gRNAs, plasmids, protein constructs, or other materials needed to evaluate engineering progress.
Prepare sequencing libraries and analyze experimental outputs to assess editing outcomes, variant performance, assay quality, and experimental reproducibility.
Troubleshoot experimental workflows and propose improvements to assay robustness, scalability, and interpretability.
Collaborate with Arbor’s computational team to apply AI-based design, analysis, modeling, and variant prioritization approaches.
Communicate experimental findings, data interpretation, and technical recommendations to project teams and cross-functional stakeholders.
Document experimental findings and contribute to patents, publications, technical reports, and regulatory documentation as appropriate.
Support technology hand-offs for assigned workstreams by summarizing methods, results, key learnings, technical risks, and recommended next steps.
Monitor emerging technologies in protein engineering, artificial intelligence, computational biology, and structural biology to help improve discovery capabilities.