Head of Platform

Head of Platform (AI / Protein Design)
Cambridge, MA | Biotechnology | Drug Discovery Platform

About the Company

A venture-backed biotechnology company is developing next-generation precision medicines through AI-guided protein design and directed evolution.

The company’s proprietary discovery platform integrates generative machine learning, large-scale protein evolution, and high-throughput screening technologies to identify novel targeting ligands capable of enabling tissue-selective intracellular delivery of therapeutic payloads, including RNA-based therapies for cardiometabolic and age-related diseases.

By combining machine learning, protein engineering, and experimental biology, the platform aims to address one of the major challenges in precision medicine: delivering therapeutics to specific tissues and cell types beyond traditional liver-targeted approaches.

As the organization continues to expand its R&D capabilities and scale its discovery platform, the company is seeking a Head of Platform to lead the development and evolution of the computational systems underpinning this technology.

The Role

The Head of Platform will lead the development and scaling of the company’s computational discovery platform supporting AI-driven protein engineering and delivery design.

This is a hands-on technical leadership role requiring deep experience in machine learning, computational biology, and protein modeling, alongside the ability to engage externally with partners and collaborators.

You will work at the intersection of machine learning, protein engineering, and experimental biology, helping translate platform innovation into therapeutic discovery programs.

Key Responsibilities

Platform Strategy & Development

• Lead the development and evolution of the computational discovery platform supporting the design and optimization of tissue-targeting proteins.

• Architect and implement machine learning models for protein design, sequence optimization, and ligand discovery.

• Integrate experimental screening data (e.g., phage display and other high-throughput assays) into model development pipelines.

• Build scalable infrastructure for protein modeling, sequence generation, and experimental feedback loops.

Hands-On Modeling & Technical Leadership

• Remain actively involved in model development, including building and deploying ML models for protein sequence–function relationships.

• Apply generative modeling, protein language models, or structural modeling approaches to design novel delivery proteins.

• Guide the application of computational tools to optimize tissue-specific targeting and intracellular delivery.

Cross-Functional Collaboration

• Partner closely with protein engineering, molecular biology, and translational teams to translate computational insights into experimental programs.

• Contribute to the design and interpretation of high-throughput screening campaigns.

External Collaboration & Scientific Representation

• Act as a technical interface with external collaborators, including pharmaceutical partners and academic groups.

• Represent the company in scientific collaborations, partnerships, and conferences.

• Contribute to publications, patents, and broader scientific communication.