VP – Machine Learning

What if… you could join an organization that creates, resources, and builds life sciences companies that invent breakthrough technologies in order to transform health care and sustainability?

FL94 Inc., is a privately held, early-stage biotechnology company pioneering Protein Editing. At FL94 we create small molecules that edit protein structure and function to unlock presently undruggable targets and a broad array of novel chemistry modalities. Our platform integrates novel small molecule chemistry and chemoproteomic discovery technologies with machine learning to enable generative design of protein editing chemistries. FL94 is backed by Flagship Pioneering, bringing the courage, vision, and resources to guide FL94 from platform validation to patient impact.We are seeking collaborative, relentless problem solvers that share our passion for impact to join us!

Position Summary:

FL94 is seeking a hands-on,n experienced, creative, and visionary Machine Learning Lead. You will be responsible for setting the strategy for, building, and leading a team of data infrastructure and machine learning scientists. The objective of this team is to develop and apply cutting-edge machine learning (ML) paradigms across FL94’s proprietary chemoproteomics and small molecule chemistry data sets to narrow the search space and increase the probability of discovering novel chemistries via generative design. This position is ideal for someone with deep expertise in machine learning, deep learning (particularly for building biologically meaningful representations of chemical structures), and computational chemistry, sciences and who is committed to building a high-preformingteam. 

Successful candidates will be able to thrive in a fast-paced, action-oriented, team environment and display a clear passion for science and impact. The role offers a unique opportunity to help drive the strategy of an early stage, big concept biotech. The candidate must be an entrepreneurial, highly motivated and purpose-driven leader who is able to strategically build high-performing teams. The successful candidate will have a track record of accomplishments in data science/machine learning as well as demonstrated high-impact research in academia or industry. S(he) must exhibit excellent leadership, project management, and strong collaboration and communication skills. S(he) should be ready to champion new ideas and lead breakthrough method development in a very dynamic and innovative environment. 

Key Responsibilities:

• Develop the vision and strategic plan for FL94’s machine learning platform, driving novel discoveries in small molecule chemistry. 
• Build and lead the data science team translating small molecule and proteomic drug discovery challenges into breakthroughs via deep learning applied to computational chemistry.
• Own the philosophy and strategy behind core machine learning technology and applications.
• Develop a robust data portal that will enable the application of generative models to proprietary chemoproteomics data.
• Define team mission and propose org structure and interaction model to ensure for successful execution.
• Oversee the development and prototyping of novel ML algorithms for drug discovery problems.
• Ensure effective training and validation of large deep learning models at scale.
• Identify and act upon new areas of applied research that can further the platform’s ability to have therapeutic impact.
• Work collaboratively in cross-functional chemistry, proteomics, drug discovery and AI/machine learning teams. 
• Partner across the organization to align data generation with infrastructure, innovative approaches, and data integration strategies. 
• Communicate strategy, R&D progress to leadership & actively engage in outreach to external advisors.
• Prepare and deliver scientific updates to the executive leadership team, board of directors, and company advisors.
• Assemble and manage machine learning and data science Scientific Advisory Boards.
• Embody FL94’s core mission to enable generative design of protein editing chemistries and live and set a culture that is highly resilient, optimistic, innovative, solutions-oriented, transparent, and inclusive.

Qualifications:

• A proven leader with a Ph.D. in machine learning, statistics, computer science, mathematical modeling, operations research, or related field computational chemistry, or other highly-technical fields from a recognized higher-education establishment.
• >3-10 years of experience in the area of computational science and artificial intelligence with track record and experience track record of solving real-world problems. Ideally candidates would have deep experience in small molecule drug discovery, talented candidates without such experience will also be considered.
• Demonstrated mastery of a broad array machine learning and deep learning approaches across a variety of deep learning architectures, deep learning libraries, and cloud-computing development environments, with an emphasis on ML techniques for studying small molecule drug development (particular attention paid to candidates with deep Graph Neural Network experience).
• Proven ability to innovate on generative machine learning models with novel architectures, deeply informed views on areas for potential creativity, and a high degree of flexibility in structuring models and workflows to adapt to experimental needs and data streams.
• Demonstrated ability to effortlessly interface with, communicate with, and motivate diverse teams of domain experts, including experimental platform builders.
• Foundational understanding of biology and chemistry in particular knowledge of chemoproteomics and small molecule drug development is preferred, but not required.
• Demonstrated ability to successfully recruit, hire, and develop a team of machine learning scientists with an emphasis on team member career growth and advancement.
• Excellent oral and written communication skills, for both technical and more general audiences.

Location:  Cambridge, MA

More About Flagship Pioneering

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. Many of the companies Flagship has founded have addressed humanity’s most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture.  Flagship has been recognized twice on FORTUNE’s “Change the World” list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies, and has been twice named to Fast Company’s annual list of the World’s Most Innovative Companies. Learn more about Flagship at www.flagshippioneering.com.

Flagship Pioneering and our ecosystem companies are 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. 

At Flagship, we recognize there is no perfect candidate. If you have some of the experience listed above but not all, please apply anyway. Experience comes in many forms, skills are transferable, and passion goes a long way. We are dedicated to building diverse and inclusive teams and look forward to learning more about your unique background.

Recruitment & Staffing Agencies: Flagship Pioneering and its affiliated Flagship Lab companies (collectively, “FSP”) do not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to FSP or its employees is strictly prohibited unless contacted directly by Flagship Pioneering’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of FSP, and FSP will not owe any referral or other fees with respect thereto.