Sr HPC Engineer

Job Summary

We are seeking a Senior HPC Engineer with deep hands-on experience in high-performance computing (HPC), hybrid cloud infrastructure, and large-scale genomic data platforms. This role will design, build, and operate scalable, high-throughput computing environments supporting clinical and research bioinformatics workflows processing tens of thousands of samples per month.

Key Responsibilities

• Lead the design and operation of scalable HPC infrastructure supporting bioinformatics pipelines.
• Develop and maintain production genomic analysis pipelines using Nextflow and related workflow tools.
• Oversee deployment and optimization of large-scale NGS analysis workflows.
• Establish best practices for pipeline reproducibility, containerization, and workflow management.
• Manage and mentor a team of bioinformatics engineers and computational scientists.
• Collaborate with lab directors/genomic scientists, bioinformaticians, and IT teams to gather requirements and design scalable solutions.
• Optimize pipeline performance, compute utilization, and data processing throughput.
• Ensure proper documentation, testing, and maintenance of bioinformatics software and workflows.
• Implement monitoring and operational best practices for production bioinformatics platforms.
• Ensure compliance with company policies and quality standards.
• Adhere to Code of Conduct as outlined in the Baylor Genetics Compliance Program.
• Perform other duties as assigned to support team and organizational objectives.

Qualifications

• PhD in Bioinformatics, Computational Biology, Computer Science, or related field preferred; MS with extensive industry experience may be considered.
• 8+ years’ experience in bioinformatics software engineering, computational genomics, or related field.
• 4+ years’ experience leading or mentoring bioinformatics or software engineering teams.
• Strong experience managing High Performance Computing (HPC) environments and distributed computing systems.
• Hands-on experience with HPC workload schedulers such as Slurm or similar cluster resource managers.
• Deep experience developing scalable workflow pipelines using Nextflow or similar workflow frameworks.
• Strong programming skills in Python, Bash, and/or R.
• Strong Linux/Unix system experience including cluster-based computing environments.
• Experience with containerization technologies such as Docker and Apptainer (Singularity).
• Experience implementing reproducible pipeline environments using container-based deployment.
• Experience with CI/CD practices, version control (Git), and automated testing.
• Experience supporting large-scale genomics datasets including WGS, WES, RNA-seq, or multi-omics pipelines.
• Experience with cloud computing platforms such as Azure or AWS is strongly preferred.
• Strong written and verbal communication skills and ability to collaborate across interdisciplinary teams.