About the Role:

Stylus Medicine is seeking an intellectually curious and creative Director, who will serve as a key scientific leader on our Platform team, owning the computational strategy that drives large serine recombinase (LSR) engineering and clinical translation. This role sits at the intersection of protein engineering, multi-omics analysis, and AI/ML-driven design and will lead a high-impact team spanning NGS and computational biology while driving the analytical infrastructure and predictive capabilities needed to advance our proprietary LSR platform from discovery through translation.

Key Responsibilities & Accountabilities:

• Lead and develop a team of NGS and computational biology scientists, setting technical direction, mentoring team members, and fostering a collaborative, high-performance culture
• Lead computational efforts to design and optimize LSRs and related genome engineering proteins for genetic medicine applications, integrating sequence-function, structure-function, and protein-DNA interaction datasets to guide engineering campaigns
• Lead analysis of NGS data from LSR experiments — including amplicon sequencing, WGS, hybrid capture, and long-read sequencing — to quantify on-target efficiency and genome-wide specificity
• Build, apply, and critically evaluate predictive and generative models for protein variant and library design — including rigorous benchmarking of AI/ML approaches such as protein language models, structure prediction tools, and generative design frameworks
• Integrate proprietary screening data with public evolutionary and structural datasets to prioritize variants and identify engineering levers for activity, specificity, and developability
• Oversee the design, implementation, and deployment of robust, scalable computational pipelines for multi-omics data analysis, ensuring accuracy, reproducibility, and maintainability
• Provide scientific input into platform strategy, translating computational insights into actionable directions for the broader team
• Partner closely with the Screening, Genome Engineering, and NGS teams to design experiments, interpret complex datasets, and refine engineering hypotheses
• Contribute to patent filings, regulatory submissions, and publications

Qualifications & Skills:

• PhD in Computational Biology, Bioinformatics, Protein Engineering, Machine Learning or a related quantitative discipline, with 10+ years or Master’s with 14+ years of industry experience
• Demonstrated research in protein modeling, protein design, or computational biology through publications, preprints, or equivalent industry contributions
• Hands-on experience applying AI/ML methods to protein variant and library design, including protein language models, structure prediction, and generative design approaches (e.g., AlphaFold2/3, RFdiffusion, ProteinMPNN, ESM)
• Expert-level proficiency in Python and/or R, with deep familiarity with data science libraries (e.g., Pandas, NumPy, Bioconductor, SciPy, PyTorch, or JAX)
• Experience with cloud computing platforms and workflow management systems
• Excellent communication and documentation skills, with a track record of effective collaboration in fast-paced, interdisciplinary environments

Pay Range; $245,000 - $265,000

About the Role

We are seeking an exceptional Staff Computational Biologist to drive the next generation of software and data products supporting Target Identification and Prioritization across our research organization. This hybrid role is ideal for someone who thrives at the intersection of biology, computation, product strategy, and engineering execution.

As a senior member of the Translational Platform Engineering team, you will act as a product owner, technical strategist, and rapid prototyper, responsible for shaping the roadmap and delivering tools that power discovery teams. Your day to day includes working with biology data scientists to harden their notebooks and workflows, pushing new releases to production (on a predictable schedule), and sitting with biologists and chemists as they use the UIs to advance our translational biology efforts. The Staff Computational Biologist is the key to translating use cases into technical specifications for engineering teams.

This is a highly visible and impactful role where you will contribute to a human-biology-first approach to drug discovery programs by leading the end-to-end lifecycle of platform capabilities used daily by our Target ID scientists.

What You’ll Do…

• Own the product roadmap for Target ID software.
• Gather and prioritize scientific requirements from internal users.
• Translate use cases into technical specifications for engineering teams.
• Rapidly prototype computational solutions using Python.
• Develop and maintain internal packages, reproducible workflows, and APIs.
• Establish documentation, onboarding materials, and best practices for internal platform usage.
• Lead cross-functional project execution (data engineering, software engineering).
• Follow good engineering practices (i.e. CI/CD, predictable demo cadence, etc.)

What You Bring...

• Bachelor's/ Master's degree in relevant field (computational biology, bioinformatics, systems biology, computer science) or equivalent relevant education and experience
• 6+ years industry experience in computational biology or data-driven discovery; minimum 1 years’ experience in software engineering and data engineering teams
• Proficiency working with programming languages Python, and R, modern development frameworks and developing internal packages
• Experience with omics/translational data analysis, scalable ETL pipelines, data modeling, and associated QC
• 1+ years’ experience leading complex projects as product owner
• Experience supporting target identification, prioritization, or multi-modal analysis.

Nice to have...

• Experience with dashboard development (e.g. Shiny, Dash, Streamlit, React, Veu.js).
• Understanding of cloud-native tools and modern data platforms (AWS/GCP/Azure).
• Familiarity with the drug discovery and development process is a plus

About the Role:

Stylus Medicine is seeking an innovative, intellectually curious and team-oriented Principal Scientist to support our large serine recombinase (LSR) engineering platform. This individual will provide high-resolution efficacy and specificity analysis to advance our pipeline as well as support onboarding of new preclinical assays for regulatory submissions, ensure accuracy of our analysis pipelines and translate our wet lab experiments into computational insights that will enable engineering of our next generation LSRs.

Key Responsibilities & Accountabilities:

• Lead the analysis of NGS data from LSR experiments (like amplicon, hybrid capture, and long-read sequencing) to quantify target efficiency and specificity
• Build integrated workflows to annotate and characterize target sites by synthesizing proprietary datasets with large-scale public genomic databases
• Design, implement, and scale robust computational pipelines for multi-omics analysis
• Collaborate closely with the Screening, Genome Engineering, and Protein Engineering teams to design experiments and interpret results
• Develop and maintain internal databases and infrastructure to ensure experimental results are accessible, reproducible, and actionable
• Contribute to patent filings, regulatory submissions, and scientific publications

Qualifications & Skills:

• PhD with 5+ years or Master’s with 10+ years (or Bachelor’s with 12+ years) of industry experience in Computational Biology, Bioinformatics, or a related quantitative discipline.
• Strong expertise in experimental design, data processing, statistical analysis, and NGS data analysis
• Expert-level proficiency in Python and/or R, with extensive experience using data science libraries (e.g., Pandas, NumPy, Bioconductor)
• Experience with cloud computing platforms for large-scale data processing and with workflow management systems
• Excellent organizational, communication, and documentation skills, with demonstrated ability to work effectively in collaborative, interdisciplinary environments
• Strong scientific critical thinking skills, including the ability to evaluate approaches, synthesize complex data, and provide actionable recommendations
• Proven track record of working successfully across cross-functional teams with proactive communication and timely delivery

Pay Range: $180,000 - $195,000

This role strongly prefers candidates located in the Boston area with the ability to regularly commute to our Seaport headquarters.

Due to the nature of this role, candidates should expect to support U.S. Government customers. Candidates must have the ability to obtain and maintain a U.S. security clearance per business requirements. In connection therewith, candidates must be willing to undergo a background investigation and meet eligibility requirements. Clearance sponsorship will be available.

Candidates who currently hold an active or recently inactive U.S. Government security clearance are encouraged to apply.

Ginkgo Biosecurity is building next-generation biosecurity infrastructure to help governments and partners detect, attribute, and deter biological threats. Our mission extends across public health, national security, and global defense, ensuring nations can rapidly identify dangerous pathogens, understand where threats originate, and respond with confidence.

We are seeking a Senior Full-Stack Software Engineer to join the Biosecurity engineering team. This role is ideal for someone who thrives in cross-disciplinary environments and is excited to build production software that directly supports biosecurity, epidemiology, and biological data workflows. We are looking for an engineer who is not only a technical expert but also a forward-thinker who embraces AI-augmented development and maintains a 'deploy-with-confidence' culture through rigorous CI/CD and automated testing

You will work across the stack—from backend services and data pipelines to user-facing web applications—building reliable, scalable systems that turn complex biological data into actionable insights.

Responsibilities

• Develop high-performance full-stack applications that translate complex biological data and operational needs into intuitive software using Python and modern JavaScript frameworks
• Champion an AI-first mindset, leveraging generative AI tools and LLM-based assistants to accelerate feature development, optimize code quality, and automate routine engineering tasks
• Collaborate with cross-functional domain experts to architect and operate on biological datasets (genomic, diagnostic, or epidemiological), ensuring that surveillance workflows maintain high standards for data integrity, provenance, and security.
• Influence the technical roadmap and long-term evolution of the Biosecurity platform, identifying and mitigating technical debt and architectural bottlenecks before they impact delivery.
• Design and implement robust CI/CD pipelines where automated unit, integration, and security testing are treated as mandatory gates for every code deployment.
• Drive engineering excellence by leading technical design reviews and providing critical feedback on software modularity, while upholding rigorous standards for documentation, observability, and long-term maintainability
• Support production systems by monitoring performance, troubleshooting issues, and continuously improving reliability, including on-call support and triage in off hours

Minimum Requirements

• 6-8+ years of professional software engineering experience, with significant full-stack development work, including ownership of complex systems and cross-team technical initiatives.
• Strong proficiency in Python for backend development (our primary programming language).
• Experience building and consuming APIs (REST and/or GraphQL).
• Experience developing modern web frontends using JavaScript/TypeScript and frameworks such as React.
• Demonstrated ability to integrate AI-assisted development tools (e.g., GitHub Copilot, Cursor, or similar) into daily workflows to increase productivity and code reliability
• Proven experience collaborating  domain experts (scientific, operations, product, etc) to translate complex biological data (genomic, diagnostic, or epidemiological) into robust software solutions and actionable insights
• Solid grounding in software engineering fundamentals: data structures, system design, version control, and modern CI/CD patterns for automated testing and deployment

Preferred Capabilities and Experience

• Prior experience in bioinformatics, computational biology, public health, or a related domain.
• Familiarity with cloud infrastructure (e.g., AWS) and containerized environments (Docker, Kubernetes).
• Experience with data pipelines, workflow orchestration, or analytics platforms.
• Exposure to regulated or sensitive-data environments (e.g., HIPAA, public health data).
• Demonstrate high levels of ownership and independent execution
• Comfort working in fast-moving, ambiguous problem spaces where requirements evolve
• Flexibility and willingness to work on the highest priority needs of the business