Principal Engineer - Sabeti Lab

Broad Institute; Cambridge (MA); Hybrid; USD 180,000 - 240,000; Full time

Job summary

The Broad Institute in Cambridge, MA is seeking an experienced computational leader to steer the lab's cloud and containerized workflows for viral discovery and virome analysis. You will shape architecture, evaluate tools, and drive scalable deployment on Terra/Manifold, while guiding cost-aware cloud strategies and collaborating with NIH/HVP partners.

You will mentor junior staff, define best practices in bioinformatics, and contribute to a cutting-edge genomics program at the Broad.

Qualifications

• Education: MSc or PhD in Computer Science, Artificial Intelligence (AI), Bioinformatics, Computational Biology, or related field, or equivalent industry experience.
• Experience: 10+ years with bachelor's degree, 8+ years with MSc, 5+ years with PhD
• Track record of leading or maintaining open-source bioinformatics software.
• Strong programming in Python and Bash; experience with ML workflows and GPUs is desirable.

Responsibilities

• Manage the architecture and long-term technical roadmap for scalable containerized workflows on Terra/Manifold for viral discovery, classification, assembly, and characterization, and lead their design, implementation, and optimization.
• Evaluate new and emerging bioinformatic tools for virome analysis and identification, decide which to adopt, and lead their integration into the group's codebase.
• Assist in defining the lab's deployment strategy for scalability and cost-efficiency on cloud infrastructure, forecasting compute and cost needs across projects.
• Serve as the lab's technical representative to the HVP consortium and external collaborators; communicate regularly with the project teams to meet deadlines and adapt workflows to emerging research needs.
• Supervise and mentor junior computational trainees and employees who are performing research, creating methods, or utilizing our tools, and identify the skills the team needs to develop.
• Serve as a subject-matter expert on evolving best practices in bioinformatics, genomics, compute infrastructure, and AI in science and engineering, and as a resource to collaborators and other Broad groups adopting them.

Skills

Ambiguity handling

Cross-functional collaboration

Open-source leadership

Education

MSc/PhD in CS/AI/Bioinformatics/Computational Biology

Tools

Docker

CI/CD pipelines

Terra

Nextflow

WDL

Cromwell

GPU/CUDA

Git

Job description

About the Broad

The Broad Institute of MIT and Harvard is a leading biomedical research institute dedicated to the bold mission of using the full power of genomics to transform the understanding and treatment of disease. The Broad Institute seeks to describe all of the molecular components of life and their connections; discover the molecular basis of major human diseases; develop effective new approaches to diagnostics and therapeutics; and disseminate discoveries, tools, methods, and data openly to the entire scientific community.

Founded in 2004 by Eric Lander and philanthropists Eli and Edythe L. Broad, the Broad Institute includes faculty, professional staff, and students from throughout the MIT and Harvard biomedical research communities and beyond, with collaborations spanning more than a hundred private and public institutions in more than 40 countries worldwide.

About the Role

This role is part of the Sabeti Lab's work as a CDC's Pathogen Genomics Center of Excellence (PGCoE) and within NIH's Human Virome Program (HVP), developing and scaling novel genomic methods to track the spread and evolution of viruses and other pathogens and characterize the largely unexplored collection of viruses and bacteriophages present in healthy humans. This role steers the technical direction for the lab's computational infrastructure and represents the lab's engineering work within the HVP consortium and to external collaborators, and advises lab leadership on computational strategy and investment.

Key Responsibilities

• Manage the architecture and long-term technical roadmap for scalable containerized workflows on Terra/Manifold for viral discovery, classification, assembly, and characterization, and lead their design, implementation, and optimization.


• Evaluate new and emerging bioinformatic tools for virome analysis and identification, decide which to adopt, and lead their integration into the group's codebase.


• Assist in defining the lab's deployment strategy for scalability and cost-efficiency on cloud infrastructure, forecasting compute and cost needs across projects.


• Serve as the lab's technical representative to the HVP consortium and external collaborators; communicate regularly with the project teams to meet deadlines and adapt workflows to emerging research needs.


• Supervise and mentor junior computational trainees and employees who are performing research, creating methods, or utilizing our tools, and identify the skills the team needs to develop.


• Serve as a subject-matter expert on evolving best practices in bioinformatics, genomics, compute infrastructure, and AI in science and engineering, and as a resource to collaborators and other Broad groups adopting them.

Requirements

• Education: MSc or PhD in Computer Science, Artificial Intelligence (AI), Bioinformatics, Computational Biology, or related field, or equivalent industry experience.


• Experience: 10+ years with bachelor's degree, 8+ years with MSc, 5+ years with PhD


• Track record of leading or maintaining open-source bioinformatics software.

Technical Skills

• Knowledge of software packaging and distribution (e.g., PyPI, Conda).


• Familiarity with containerization (Docker) and CI/CD pipelines.


• Experience using Terra or other cloud-based platforms for large-scale genomic analysis, including cost management at scale.


• Proficiency in writing WDL or Nextflow workflows and working with workflow engines like Cromwell or miniWDL on cloud platforms.


• Strong programming skills in Python and bash, including hands-on experience with machine learning workflows (e.g., scikit-learn, PyTorch, or TensorFlow). Familiarity with training and inference on GPUs, managing CUDA environments, and optimizing ML performance in a high-throughput setting is highly desirable.


• Familiarity with git and collaborative software development practices.


• Proficiency in agentic coding tools, practices, and harnesses.

Competencies

• Ability to take on ambiguous, open-ended problems with minimal oversight, manage tasks efficiently, and collaborate with interdisciplinary teams.


• This is a hybrid position. Must have the ability to work in person at the Broad Institute at least 3 days a week.

The expected base pay range for this position as listed above is based on a 40 hour per week schedule. Broad provides pay ranges representing its reasonable and good faith estimate of what the organization reasonably expects to pay for a position at the time of posting. Actual compensation will vary based on factors including but not limited to, relevant skills, experience, education, qualifications, and other factors permissible by law.

At Broad, your base pay is just one part of a comprehensive total rewards package. From day one, this role offers a competitive benefits package including medical, dental, vision, life, and disability insurance; a 401(k) retirement plan; flexible spending and health savings accounts; at least 13 paid holidays; winter closure; paid time off; parental and family care leave; and an employee assistance program, among other Broad benefits.

The Broad Institute is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, disability, protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations.

Should you need a reasonable accommodation to complete the application or interview process, please contact [e-mail] for assistance.