Ampersand Biomedicines
Principal Scientist, AI Protein Design
Ampersand Biomedicines, Boston, Massachusetts, us, 02298
Overview
Ampersand Biomedicines is an innovative, privately held biotechnology company leading in developing multi-specific medicines that direct therapeutic molecules to specific cells and biological contexts. Ampersand was founded in Flagship Pioneering’s venture creation engine, where companies such as Moderna Therapeutics and Seres Therapeutics were conceived and created. Ampersand cultivates a highly dynamic and entrepreneurial environment. Position Summary
We are seeking a creative and motivated scientist with expertise in machine learning-driven antibody binder design to join Ampersand’s Computational Science team. This role demands a strong foundation in machine learning/deep learning and sequence/structure-based protein design. As a Principal Scientist, Machine Learning, you will be responsible for developing the frameworks and core models that propel our antibody design process forward. This is an opportunity to be part of a cutting-edge biotech company at the forefront of computational antibody design. You will play a pivotal role in shaping our AND-Body platform, working closely with expert biologists, protein scientists, and computational biologists to push the boundaries of antibody discovery. This position requires full-time, on-site presence to facilitate interactions with other team members and maximize impact. Responsibilities
Design and conduct independent machine learning research to promote antibody binder design. Deliver robust, production-quality models that will drive the next generation of antibody design, advancing both engineering and de novo design. Collaborate closely with experimental teams to align with their capabilities, enabling the creation of advanced hybrid platforms. Communicate insights and conclusions to colleagues in the scientific and leadership teams. Manage members of the Machine Learning team to drive advancements in our AND-Body platform. Develop a high-performing and ambitious team by providing mentorship, growth opportunities, and clear career development pathways for direct reports. Foster a culture of collaboration and accountability through strong cross-functional communication, ensuring alignment with key stakeholders and driving business success. Contribute to building a positive, team-oriented biotech culture. Qualifications
A PhD in biochemistry, biophysics, computational chemistry, computational biology, computer science, machine learning, or a related discipline solving biological or chemical problems using computational approaches. Strong background and demonstrated experience in machine learning/deep learning, modeling, simulation, and design, particularly in sequence and structure-based antibody design. Demonstrated experience with tools for protein design and machine learning approaches (AlphaFold, ESM, ProteinMPNN, RF-Diffusion, Rosetta, etc.). Demonstrated experience in Python and standard ML tools (PyTorch, TensorFlow, JAX, PyG, PyMC, etc.). Experience with developing novel AI, structure, or sequence-based methods for biomolecular design. Preferred
5+ years of industry experience that includes significant work in machine learning, especially in antibody or protein binder design. Strong communication skills, with the ability to translate complex computational findings into actionable insights within a collaborative group setting. Experience working in an interdisciplinary environment, effectively collaborating with bench scientists, with the ability to think independently and contribute to a dynamic intellectual environment. Expertise with common software development tools and best practices: Git, AWS or other cloud experience, testing frameworks, etc. Proven track record of successfully managing protein design related machine learning projects with multiple team members. Experience with workflow tools such as Dask, Prefect, MLFlow, etc. Ability to multi-task and prioritize in a fast-paced start-up setting. About Flagship
Flagship Pioneering is a bioplatform innovation company that invents and builds platform companies, each with the potential for multiple products that transform human health or sustainability. Since its launch in 2000, Flagship has originated and fostered more than 100 scientific ventures, resulting in more than $90 billion in aggregate value. Flagship has been recognized on Fortune’s Change the World list and Fast Company’s World’s Most Innovative Companies list. Learn more about Flagship at www.flagshippioneering.com. Equal Employment Opportunity
Flagship Pioneering is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or veteran status.
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Ampersand Biomedicines is an innovative, privately held biotechnology company leading in developing multi-specific medicines that direct therapeutic molecules to specific cells and biological contexts. Ampersand was founded in Flagship Pioneering’s venture creation engine, where companies such as Moderna Therapeutics and Seres Therapeutics were conceived and created. Ampersand cultivates a highly dynamic and entrepreneurial environment. Position Summary
We are seeking a creative and motivated scientist with expertise in machine learning-driven antibody binder design to join Ampersand’s Computational Science team. This role demands a strong foundation in machine learning/deep learning and sequence/structure-based protein design. As a Principal Scientist, Machine Learning, you will be responsible for developing the frameworks and core models that propel our antibody design process forward. This is an opportunity to be part of a cutting-edge biotech company at the forefront of computational antibody design. You will play a pivotal role in shaping our AND-Body platform, working closely with expert biologists, protein scientists, and computational biologists to push the boundaries of antibody discovery. This position requires full-time, on-site presence to facilitate interactions with other team members and maximize impact. Responsibilities
Design and conduct independent machine learning research to promote antibody binder design. Deliver robust, production-quality models that will drive the next generation of antibody design, advancing both engineering and de novo design. Collaborate closely with experimental teams to align with their capabilities, enabling the creation of advanced hybrid platforms. Communicate insights and conclusions to colleagues in the scientific and leadership teams. Manage members of the Machine Learning team to drive advancements in our AND-Body platform. Develop a high-performing and ambitious team by providing mentorship, growth opportunities, and clear career development pathways for direct reports. Foster a culture of collaboration and accountability through strong cross-functional communication, ensuring alignment with key stakeholders and driving business success. Contribute to building a positive, team-oriented biotech culture. Qualifications
A PhD in biochemistry, biophysics, computational chemistry, computational biology, computer science, machine learning, or a related discipline solving biological or chemical problems using computational approaches. Strong background and demonstrated experience in machine learning/deep learning, modeling, simulation, and design, particularly in sequence and structure-based antibody design. Demonstrated experience with tools for protein design and machine learning approaches (AlphaFold, ESM, ProteinMPNN, RF-Diffusion, Rosetta, etc.). Demonstrated experience in Python and standard ML tools (PyTorch, TensorFlow, JAX, PyG, PyMC, etc.). Experience with developing novel AI, structure, or sequence-based methods for biomolecular design. Preferred
5+ years of industry experience that includes significant work in machine learning, especially in antibody or protein binder design. Strong communication skills, with the ability to translate complex computational findings into actionable insights within a collaborative group setting. Experience working in an interdisciplinary environment, effectively collaborating with bench scientists, with the ability to think independently and contribute to a dynamic intellectual environment. Expertise with common software development tools and best practices: Git, AWS or other cloud experience, testing frameworks, etc. Proven track record of successfully managing protein design related machine learning projects with multiple team members. Experience with workflow tools such as Dask, Prefect, MLFlow, etc. Ability to multi-task and prioritize in a fast-paced start-up setting. About Flagship
Flagship Pioneering is a bioplatform innovation company that invents and builds platform companies, each with the potential for multiple products that transform human health or sustainability. Since its launch in 2000, Flagship has originated and fostered more than 100 scientific ventures, resulting in more than $90 billion in aggregate value. Flagship has been recognized on Fortune’s Change the World list and Fast Company’s World’s Most Innovative Companies list. Learn more about Flagship at www.flagshippioneering.com. Equal Employment Opportunity
Flagship Pioneering is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or veteran status.
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