Who We Are
Flagship Pioneering is a biotechnology company that invents and builds platform companies that change the world. We bring together the greatest scientific minds with entrepreneurial company builders and assemble the capital to allow them to take courageous leaps. Those big leaps in human health and sustainability exponentially accelerate scientific progress in areas ranging from cancer detection and treatment to nature-positive agriculture.
What sets Flagship apart is our ability to advance biotechnology by uniting life science innovation, company creation, and capital investment under one roof in a way that is largely without precedent. Our scientific founders, entrepreneurial leaders, and professional capital managers are each aligned around an institutionalized process that enables us to innovate and transform for the benefit of people and planet.
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.
Position Summary
We believe deep integration of data-driven machine learning with experimental approaches is a core driver of the next generation of defining companies in health. We imagine this will be driven by individuals from diverse scientific and machine learning backgrounds. Thus, we are open to all profiles with computational excellence.
We are seeking the most innovative and entrepreneurial Machine Learning Scientists. You will join organizations at the early stages of our company creation process to develop innovative algorithmic methods, leveraging both in-house and external data to train and evaluate models while also deploying new algorithms into production and integrating deeply into experimental platforms to close feedback loops. The successful candidate will work closely with experimental scientists to rapidly advance various scientific programs.
Key responsibilities:
- Develop or fine-tune deep learning architectures and hone them through deployment on experimental platforms.
- Work with experimental groups to integrate modeling efforts into high-impact applications.
- Develop production-quality code in a team setting and plan for deploying and training models at scale.
- Present progress from scientific work in regular research meetings and prepare reports and slide decks for broader internal and external communication.
Qualifications:
- PhD in computer science with a desire to collaborate with leading experimentalists or a PhD in scientific field plus demonstrated experience applying deep learning. Exceptional candidates without PhDs will be considered.
- Experience developing, debugging, and applying models using modern deep learning frameworks on GPUs in cloud environments.
- Proficiency in Python and machine learning frameworks such as TensorFlow, Pytorch, and/or JAX.
- Desire to work across the entire data stack, from data ingest to model deployment.
- Curiosity and humility to work with scientific domain experts to identify and frame problems worth solving beyond existing benchmarks.
- Energetic self-starter with the ability to work effectively in a startup environment.
- Excellent analytical skills and ability to synthesize & communicate complex information rapidly and effectively.
Location: Cambridge, MA
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.