Job Description
Job DescriptionOur client, a biotech startup in Boston, Massachusetts, is seeking a highly skilled engineer to develop and maintain a genomic diagnostics platform, transforming raw genomic and scientific datasets into clinically actionable insights. The role involves backend development, workflow orchestration, and cloud infrastructure, with a strong emphasis on scientific computing and analytical pipelines. The ideal candidate will collaborate closely with scientists, bioinformaticians, and cross-functional teams to build scalable, production-ready pipelines in a regulated, clinical environment.
Employment Type: Full-time permanent
Location: Hybrid (Boston, Massachusetts) - Open to North America. Relocation assistance and visa sponsorship available
Compensation: $220,000-250,000 base annually + bonus + equity
What You'll Do:
- Develop and maintain a genomic diagnostics platform and associated backend systems.
- Lead or own pipeline and workflow architecture in production environments.
- Design, implement, and optimize analytical pipelines for large-scale scientific or genomic datasets, including ingestion, transformation, validation, and distributed processing.
- Work with workflow orchestration tools such as WDL, Cromwell, Nextflow, Airflow, or equivalents.
- Build cloud-based backend systems, ideally on GCP, capable of handling large volumes of sequential data processing.
- Ensure containerization and reproducibility of pipelines using Docker or other container technologies.
- Maintain strong PHI handling, data privacy, and compliance practices in scientific or clinical environments.
- Collaborate with cross-functional teams to translate complex analytical requirements into scalable engineering solutions.
- Focus on scientific computing, HPC-style workflows, and large-scale data ingestion systems.
RequirementsWhat You'll Bring:
- 7-10+ years of software engineering experience in life sciences, diagnostics, scientific computing, or genomics.
- 6+ years of professional software engineering experience with a focus on scientific computing, analytical pipelines, HPC-style workflows, or large-scale data ingestion systems.
- Demonstrated ability to lead or own pipeline and workflow architecture in production environments.
- Expertise with large scientific or genomic datasets, including ingestion, transformation, validation, and distributed processing.
- Experience processing raw scientific data such as genomic reads, image data, or sensor data.
- Deep experience with workflow orchestration (WDL, Cromwell, Nextflow, Airflow, or equivalent).
- Proven background building cloud-based backend systems in GCP, supporting large volumes of sequential data processing.
- Experience with GCP Batch or distributed compute frameworks.
- Experience with containerization and reproducibility (Docker, containerized scientific pipelines).
- Strong understanding of PHI handling, data privacy, and compliance within scientific or clinical environments.
- Ability to work closely with scientists, bioinformaticians, and cross-functional teams to convert complex analytical requirements into scalable engineering solutions.
- Familiarity with scientific computing libraries (PyTorch, NumPy, Pandas, statistical modeling).
- Expertise in monitoring scientific workloads at scale (Prometheus, Grafana, or equivalent).
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