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Salary: USD 135,000 - 150,000 / annual
Arbor Biotechnologies, a clinical-stage gene editing company based in Cambridge, MA, is seeking a Senior Scientist to drive protein engineering workstreams for next-generation genome editing tools. The company is advancing a portfolio of first-in-class genomic medicines addressing serious diseases including ALS and primary hyperoxaluria type 1, leveraging a unique breadth of gene editing technologies.
In this role, you will design and execute protein engineering experiments to generate best-in-class molecules. You will play a key role in selecting protein mutants and variants, testing them in cellular and biochemical screens, analyzing downstream data, and communicating results within the team and cross-functionally.
Key responsibilities include:
**Protein Engineering Design & Execution:** Drive defined workstreams within protein engineering campaigns, including design, generation, and evaluation of protein mutants and variants. Recommend experimental approaches and follow-up studies in collaboration with project leads. Select and apply protein engineering strategies such as rational design, structure-guided engineering, and deep mutational scanning based on project goals. Independently design and execute experiments to test protein engineering hypotheses and evaluate variant performance. Analyze experimental results and recommend next steps to support iterative design-build-test-learn cycles.
**Protein Biochemistry & Structure-Function Analysis:** Apply structure-guided protein engineering approaches using experimental structures, homology models, and AI-predicted structures to generate and prioritize variant hypotheses. Use protein structure visualization and molecular modeling tools (PyMOL, ChimeraX, AlphaFold-derived models) to analyze active sites, protein-protein interfaces, and sequence-structure-function relationships. Design and perform biochemical assays to investigate protein properties including activity, stability, specificity, and kinetics. Interpret biochemical and cellular assay results to support protein engineering decisions.
**Screening Workflows & Experimental Characterization:** Develop, optimize, and execute cell-based screening workflows using transient transfection, nucleofection, transduction, and other approaches in dividing and non-dividing cell models. Build or improve high-throughput screening strategies to increase experimental throughput and data quality. Design, order, and generate reagents including AAVs, mRNA, gRNAs, plasmids, and protein constructs. Prepare sequencing libraries and analyze experimental outputs to assess editing outcomes and variant performance. Troubleshoot experimental workflows and propose improvements to assay robustness and scalability.
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. 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 comfortable combining hands-on experimentation with data analysis, structural insight, and collaborative problem-solving.
**Requirements:**
The posting does not explicitly state years of experience or formal education requirements. However, the role expects: strong scientific judgment and independent execution; expertise in protein engineering strategies (rational design, structure-guided engineering, deep mutational scanning); proficiency with protein structure visualization tools (PyMOL, ChimeraX) and AI-predicted structure models (AlphaFold); hands-on experience designing and executing biochemical assays; experience with cell-based screening workflows and molecular biology techniques (transfection, nucleofection, transduction); ability to design and generate molecular biology reagents (AAVs, mRNA, gRNAs, plasmids); experience with sequencing library preparation and data analysis; detail-oriented and motivated with willingness to learn; flexible mindset; clear communication; team-first attitude; data-driven mindset; and comfort with ambiguity and collaborative problem-solving.
