Impress employers and recruiters.
Choose from hundreds of resume examples.

Target Resume Now

About the Role

Manifold Bio is seeking an engineer to own and evolve its AI research compute platform, built on AWS EKS, Ray, and Kubernetes. This role involves ensuring the security, uptime, and cost-efficiency of the platform while optimizing model runtimes and developing features to enhance scientist productivity. The position also includes building infrastructure for internal agentic workflows and working with AI tooling for rapid iteration.

Responsibilities

Own and develop Manifold's EKS-based compute platform to meet the shifting needs of computational sub-teams, including mBER development and production runs, LLM fine-tuning, and novel binder design research.
Monitor AWS compute costs and implement optimizations to reduce spend while supporting growth.
Run and optimize production models (mBER, folding models, and other generative models) for fast iteration and a consistent library design cycle.
Improve security, uptime, and cross-region access across the compute stack, hardening infrastructure against external threats.
Establish CI/CD practices (likely GitOps) and clear, comprehensive cost-tracking.
Build and maintain platforms for agentic automation and custom internal agentic workflows.
Help define the data handoff from AI generation to Snowflake + Benchling and connect to experimental readouts.

Requirements

Strong, ML-specific coding skills in PyTorch and/or JAX, with the ability to quickly prototype, test, and debug.
Strong familiarity with AWS, especially EC2, EKS, networking, and storage solutions.
Experience optimizing GPU-heavy computational workloads.
Strong security practices and experience hardening web applications and infrastructure against external attackers.
Deep integration with agentic AI development tools.
Experience building and working with relational databases.
Ability to move fast - standing up prototypes and iterating in production with a diverse user base.
Strong data science and analysis skills.
Interest in bio-specific ML, with a background in physical or natural sciences.
Track record of advanced automation using agentic AI tooling.
Experience with transformer architectures or graph neural networks for molecular data.
Published research in ML, computational biology, or protein design.
Knowledge of protein engineering, directed evolution, or structural biology wet lab techniques.
Previous biotech/pharma industry experience.

Skills

PyTorch
JAX
AWS
EC2
EKS
Kubernetes
Ray
CI/CD
GitOps
Snowflake
Benchling
Agentic AI tooling
Transformer architectures
Graph neural networks
MLOps

Location

Boston, Massachusetts
San Francisco, California

Work Type

On-site

Experience Level

Mid-level

About the Company

Manifold Bio is a platform biotechnology company pioneering AI-guided protein design and massively multiplexed in vivo screening to unlock tissue-targeted medicines and organism-scale models of living systems.
Using proprietary molecular barcoding technology, we screen hundreds of thousands of protein designs simultaneously in living systems, producing in vivo-validated datasets at a scale no one else can match.
The datasets power our computational models, which leads to better drug designs, creating a flywheel that gets stronger with every campaign.
Our team of protein engineers, biologists, and computational scientists works across this full stack to pursue programs both internally and with leading pharma companies.

Equal Opportunity

We value different experiences and ways of thinking and believe the most talented teams are built by bringing together people of diverse cultures, genders, and backgrounds.