**Machine Learning Expert**
7 days ago
Develop innovative algorithmic methods using both in-house and external data to train and evaluate models, deploying new algorithms into production and integrating deeply into experimental platforms to close feedback loops.
Requirements:
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.
What We Offer:
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.
About Us:
Flagship Pioneering is a bioplatform innovation 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.
We are seeking the most innovative and entrepreneurial Machine Learning Scientists 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, developing production-quality code in a team setting and planning for deploying and training models at scale. The candidate will present progress from scientific work in regular research meetings and prepare reports and slide decks for broader internal and external communication.
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.
About Our Location:
Cambridge, MA is a hub for biotech and life sciences innovation, and we are seeking a Machine Learning Scientist to join our team in this vibrant and dynamic location.
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.
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