Machine Learning Scientist, Protein Design
SkyhookUnited States3 hours ago
Full-timeOther
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About Skyhook Bio:
Skyhook accelerates the discovery and development of differentiated therapeutics by accessing vast biological design spaces previously intractable with current state of the art technologies. Our differentiated platform employs efficient AI-guided design, synthesis, and functional screening of diverse programmable biomolecule libraries at unprecedented speed and scale.
About the Role:
We are seeking a collaborative and motivated Machine Learning Scientist with a passion for working at the intersection of human and synthetic biology. In this role, you will develop deep-learning methods and models to design functional proteins and analyze large proprietary data sets from high-throughput functional assays. As part of a growing multidisciplinary team, you will have the opportunity to take part in leading innovative research and development in a dynamic startup environment.
Key Responsibilities:
Raven is RA Capital’s healthcare incubator. From discovery to delivery, whether Raven incubates, accelerates or rejuvenates, Raven’s goal is to turn scientific breakthroughs into transformative therapies and get them quickly, safely and efficiently to the patients that need them most. Raven’s experienced scientists, operators, and healthcare innovators have deep sector expertise across therapeutics, diagnostics, devices and services. They have brought hundreds of therapeutics into development, managed hospital systems, optimized clinical trials and navigated payor and regulatory systems to deliver patient impact - and they are ready to work with you.
About RA Capital:
Founded in 2004, RA Capital Management is a multi-stage investment manager dedicated to evidence-based investing in public and private healthcare, life sciences, and planetary health companies. RA Capital creates and funds innovative companies, from private seed rounds to public follow-on financings, allowing management teams to drive value creation from inception through commercialization and beyond. RA Capital's knowledge engine is guided by our Tech Atlas internal research division, and Raven, RA Capital’s company building team, offers entrepreneurs and innovators a collaborative and comprehensive platform to explore the novel and the re-imagined. RA Capital has more than 150 employees and over $10 billion in assets under management.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Skyhook accelerates the discovery and development of differentiated therapeutics by accessing vast biological design spaces previously intractable with current state of the art technologies. Our differentiated platform employs efficient AI-guided design, synthesis, and functional screening of diverse programmable biomolecule libraries at unprecedented speed and scale.
About the Role:
We are seeking a collaborative and motivated Machine Learning Scientist with a passion for working at the intersection of human and synthetic biology. In this role, you will develop deep-learning methods and models to design functional proteins and analyze large proprietary data sets from high-throughput functional assays. As part of a growing multidisciplinary team, you will have the opportunity to take part in leading innovative research and development in a dynamic startup environment.
Key Responsibilities:
- Develop and advance deep-learning methods to design and optimize proteins
- Train and evaluate machine learning models using proprietary high-throughput assay data and public protein sequence, structure, and function datasets
- Design and deploy active learning strategies to accelerate protein design cycles
- Analyze large-scale experimental datasets to extract insights and inform protein engineering strategy
- Collaborate closely with experimental and computational scientists to integrate laboratory and in silico workflows, including NGS-based analyses
- Communicate computational strategies, results, and recommendations to multidisciplinary teams and leadership
- PhD in Computer Science, Machine Learning, Computational Biology, Biophysics, Bioinformatics, Statistics, or related field. 2+ years industry experience in pharma or biotech R&D preferred. Position leveling will be commensurate with experience
- Strong foundation in machine learning, including model development, training, evaluation, and application to large-scale biological datasets
- Experience with exploratory data analysis, statistical analysis, and data visualization to interpret experimental results and guide modeling decisions
- Proficiency in modern ML frameworks such as PyTorch or TensorFlow, and writing efficient, well-structured, and maintainable code (Python required)
- Experience working with cloud-based ML workflows and data pipelines (AWS preferred)
- Strong analytical and problem-solving skills; comfortable working in a dynamic, collaborative startup environment
- Clear written and verbal communication skills, with the ability to explain technical concepts to diverse audiences
- Experience with protein-focused ML models and tools (e.g., ESM, AlphaFold, or related frameworks)
- Experience designing or improving ML infrastructure and data pipelines, including cloud-based training, inference, data versioning, automation, and deployment
- Experience with NGS data analysis pipelines and integrating experimental data with computational workflows
Raven is RA Capital’s healthcare incubator. From discovery to delivery, whether Raven incubates, accelerates or rejuvenates, Raven’s goal is to turn scientific breakthroughs into transformative therapies and get them quickly, safely and efficiently to the patients that need them most. Raven’s experienced scientists, operators, and healthcare innovators have deep sector expertise across therapeutics, diagnostics, devices and services. They have brought hundreds of therapeutics into development, managed hospital systems, optimized clinical trials and navigated payor and regulatory systems to deliver patient impact - and they are ready to work with you.
About RA Capital:
Founded in 2004, RA Capital Management is a multi-stage investment manager dedicated to evidence-based investing in public and private healthcare, life sciences, and planetary health companies. RA Capital creates and funds innovative companies, from private seed rounds to public follow-on financings, allowing management teams to drive value creation from inception through commercialization and beyond. RA Capital's knowledge engine is guided by our Tech Atlas internal research division, and Raven, RA Capital’s company building team, offers entrepreneurs and innovators a collaborative and comprehensive platform to explore the novel and the re-imagined. RA Capital has more than 150 employees and over $10 billion in assets under management.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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