B.S. in Computer Science, Software Engineering, Bioinformatics, or a related technical field
At least 8 years of professional software engineering experience, including work on production systems and data-intensive applications
Demonstrated ability to collaborate effectively with interdisciplinary teams of different technical and scientific backgrounds
Extensive experience with Python, including development of complex data pipelines and use of applicable software libraries
Experience working with large, heterogeneous biological datasets in Python (HDF5, Parquet, PyArrow , xarray ) -ideally in genomics or biomedical contexts
Experience building and operating distributed compute workflows and orchestration systems (e.g., Celery, Dask , SLURM, Nextflow , Snakemake ) for large-scale genomic or biomedical data processing
Strong experience with relational databases such as PostgreSQL or MySQL, including schema design and query optimization
Experience with containerization and cloud-native infrastructure technologies such as Docker and Kubernetes
Familiarity with machine learning frameworks and tools, including scikit-learn and PyTorch
Demonstrated experience with the full software development lifecycle (SDLC), including testing, CI/CD, version control, and deployment
Background working in computational biology, bioinformatics, or a related field, with experience developing software that supports biological research
Related Skills & Other Requirements
Excellent communication skills, with the ability to engage technical and non-technical audiences, including senior leadership.
Strong cross-functional collaboration skills, with a track record of working effectively with non-engineering stakeholders to translate needs into software solutions.
Deep curiosity about science and a passion for building tools that empower scientific discovery.
Advanced degree in Computer Science, Engineering, Bioinformatics, or a related field.
Expertise in bioinformatics, including experience with genomic data processing, analysis pipelines, and related computational methods.
Familiarity with AWS or other major cloud platforms.
Experience with high-performance computing (HPC) environments.
REQUIRED
Additional Information
POSITION SUMMARY
The Center for Computational Biology (CCB) is seeking an experienced senior software engineer to join a growing team of developers within CCB and the other centers across the Flatiron Institute who help build and maintain HumanBase . HumanBase is a dynamic and interactive web-based platform that supports thousands of biomedical researchers in exploring the molecular mechanisms of human disease. This position is ideal for an experienced engineer with bioinformatics experience who thrives on solving complex problems at the intersection of large-scale data, pipeline building, advanced analytics, and scientific discovery. This is a high-impact role that directly advances the study of human genomics and disease.
The successful candidate will collaborate closely with researchers at the Center for Computational Biology to translate cutting-edge computational biology research into scalable production systems and data pipelines that power HumanBase . This is a hands-on backend role for an experienced engineer with expertise in biological data, genomics, and -omics technologies. They will also have experience processing large-scale -omics datasets, maintaining production software systems, designing and optimizing data-intensive pipelines, and supporting machine learning workflows in scientific computing environments.
This is a full-time position based in the Simons Foundation offices in New York City. Visit the Simons Foundation career page to learn more.
ESSENTIAL FUNCTIONS/RESPONSIBILITIES
Contribute to the design, architecture, and implementation of new HumanBase features and major infrastructure improvements
Translate research-stage computational methods into robust, maintainable, and reproducible production software and data pipelines
Design, develop, and optimize scalable genomics and biomedical data processing pipelines that ingest, normalize, and transform heterogeneous datasets
Integrate machine learning and statistical methods into production workflows for analysis of complex biological datasets
Apply software engineering best practices, including code review, testing, version control, documentation, CI/CD, and deployment automation
Collaborate closely with computational biologists, data scientists, and external partners to align engineering efforts with scientific and platform goals
Evaluate and adopt emerging technologies in bioinformatics, cloud infrastructure, and scientific computing where appropriate to improve platform capabilities and performance
Contribute to operational support, maintenance, and continuous improvement of production systems supporting HumanBase
Perform other duties or tasks as assigned or required
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