AI Engineer - Metabolic Sensor Design

Primary Work Address: 19700 Helix Drive, Ashburn, VA, 20147

Current HHMI Employees, click here to apply via your Workday account.

Intro:

AI@HHMI: HHMI is investing $500 million over the next 10 years to support AI-driven projects and to embed AI systems throughout every stage of the scientific process in labs across HHMI. The AI initiative will be centered at HHMI's Janelia Research Campus. Janelia has been at the forefront of AI-driven research in biology for more than 15 years. Its forward-thinking structure, centralized funding, and collaborative culture make it ideally suited to take this bold leap forward. To learn more about the initiative, visit here.

Please include a cover letter with your application detailing your qualifications and experience as they relate to this position. Please include a description of one related deep learning model or framework (e.g., AlphaFold, ESM, Chai-1, Boltz-1, etc.) that you have used. Briefly describe what you used it for and tell us about limitations and challenges you encountered.

About the role:

The CombinAItorial Sensor Design project is part of HHMI's AI for Science Initiative (ai.hhmi.org) and brings together expertise in protein engineering, advanced microscopy, and machine learning. Our goal is to develop a protein biosensor optimization pipeline that integrates high-throughput functional screening with predictive deep learning to accelerate the directed evolution of protein biosensors for visualizing dynamic biochemical processes in living cells.

We are seeking a highly skilled AI Software Engineer to join our team and play a crucial role in advancing our AI-driven scientific initiatives. In this position, you will be responsible for developing and maintaining the computational infrastructure essential for AI-powered biosensor optimization. You will collaborate with data scientists and experimentalists to develop robust data flows from optical pooled screening outputs through to model training and deployment. You will implement cutting-edge tools for predicting fluorescence properties and biochemical performance based on protein sequence and structure. This role requires close collaboration with our microscopy, sequencing, and protein engineering team to ensure the seamless integration of computational and experimental workflows.

Strong programming skills in Python, PyTorch, and JAX are required. Familiarity with protein modeling or machine learning frameworks such as AlphaFold, ESM, Chai-1, or Boltz-1 is highly valued. We are looking for candidates with experience in ML model deployment, workflow orchestration, and high-throughput data processing, as well as experience working with large biological datasets in GPU-based computing environments.

What we provide:

• A competitive compensation package, with comprehensive health and welfare benefits.
• A supportive team environment that promotes collaboration and knowledge sharing.
• The opportunity to engage with world-class researchers, software engineers and AI/ML experts, contribute to impactful science, and be part of a dynamic community committed to advancing humanity's understanding of fundamental scientific questions.
• Amenities that enhance work-life balance such as on-site childcare, free gyms, available on-campus housing, social and dining spaces, and convenient shuttle bus service to Janelia from the Washington D.C. metro area.

• Develop and maintain computational infrastructure and predictive tools for AI biosensor optimization, including tool development for modeling fluorescence properties and biochemical performance from sequence and structure
• Collaborate with other team members to ensure seamless integration of computational and experimental aspects of the project.
• Apply machine learning, AI techniques, and software engineering best practices to deliver scalable, maintainable, and reproducible AI systems for protein engineering
• Carefully document data, code, and processing pipelines to enable seamless reproduction and extension of research results
• Actively contribute to the latest advancements in the field and continuously improve your skillset with the latest advances in AI research and technologies.
• Collaborate with interdisciplinary teams, potentially mentor junior engineers, and direct or assist in directing the work of others to meet project goals while advising stakeholders on data strategies and best practices.

• Bachelor's degree in Computer Science, Data Science, Statistics, Applied Mathematics, or a related field; or an equivalent combination of education and relevant experience.
• 3+ years of experience in developing and fine-tuning deep learning models.
• Strong programming skills in Python, PyTorch, and JAX.
• Familiarity with protein modeling deep learning frameworks (e.g., AlphaFold, ESM, Chai-1, Boltz-1).
• Familiarity with computer vision deep learning frameworks (e.g., SAM, cellpose)
• Experience with ML model deployment, workflow orchestration, and high-throughput data processing.
• Excellent technical documentation and communication skills, with the ability to convey complex data concepts to both technical and non-technical audiences.
• A detail-oriented, creative, and organized team player with a collaborative mindset.