Director, AI/ML

About us:

Launched by RA Capital, Skyhook is building a modular, next-gen platform to unlock previously unavailable biomolecule design spaces to accelerate the discovery and development of differentiated therapeutic, diagnostic, and industrial products. Our team is an innovative group of domain experts in AI/ML computational design, advanced synthetic biology, microfluidics, protein engineering, and single-cell profiling who are deeply passionate about the power of the platform to invent the future today. World-class scientific founders from the Broad Institute, cutting-edge technology, and backing from RA Capital come together in a dynamic start-up environment.

About RA Capital:

RA Capital funds and builds healthcare and life science companies using an evidence-based investment approach informed by TechAtlas, a think tank within RA Capital which analyzes scientific and clinical data from academic literature and industry sources to anticipate how breakthroughs might impact industry stakeholders, physicians, patients, and policymakers. TechAtlas' analyses are captured in a unique collection of competitive landscapes, or ‘maps’, that identify competitive therapeutics, diagnostics, research tools, and/or technological capabilities in a given area.

About the Role:

We are seeking an innovative, self-driven, and team-oriented Director in Artificial Intelligence / Machine Learning (AI/ML), with a passion for developing cutting-edge platforms at the intersection of AI/ML, protein engineering, synthetic biology, and single-cell technologies. In this role, you will play a pivotal role in shaping and driving the vision, strategy and execution of our AI/ML platform. You will oversee the development and deployment of innovative machine learning solutions, build robust IT infrastructure, and lead a talented team of AI/ML scientists. As a key member of a growing and engaged team, you will have the opportunity to take part in leading innovative research and development, and collaborate with a highly skilled, multidisciplinary team in a fast-paced startup environment.

Key Responsibilities:

• Develop a comprehensive vision and strategic plan for the AI/ML platform
• Mentor and lead a multidisciplinary AI/ML team to build advanced protein design and machine learning tools
• Create a data-driven organization by collaborating closely with cross functional teams to integrate AI/ML into workflows, and design data generation experiments and pipelines to support machine learning needs
• Oversee the evaluation, training and deployment of deep neural network models using both proprietary and external protein sequence, structure, and function data
• Oversee the development and application of deep-learning models to analyze high dimensional biological datasets, including transcriptomics, proteomics, and multi-omics single-cell data
• Implement scalable IT infrastructure to support active learning systems and machine learning workflows, including data pipelines, model training and deployment
• Communicate the AI/ML strategy, progress, and results to internal and external stakeholders, including the leadership team and investors
  
  
  

Qualifications & Skills:

• PhD in Computer Science, Machine Learning, Computational Biology, Bioinformatics, Statistics, or a related field
• Proven track record of developing and deploying AI/ML solutions in complex, data-rich environments
• Deep understanding of machine learning models for protein design such as ESM, AlphaFold, etc
• Experience with conceiving of, implementing, and maintaining active learning systems for rapid design and development of product candidates
• Experience in machine learning infrastructure, pipeline building, database maintenance, distributed training and inference, and deployment in cloud computing such as AWS
• Significant experience in data science and developing and deep learning models and algorithms using software libraries such as PyTorch, TensorFlow, or similar
• Experience working with large biological datasets, including multi-omics single cell sequencing data
• Strong analytical skills, detail-oriented, and thrives in a fast-paced startup environment
• Excellent communication skills (written and verbal) and adept at building strong relationships across multidisciplinary teams