Senior Machine Learning Scientist

Position Summary:

Cellarity is looking for a Senior Machine Learning Scientist enthusiastic about solving complex questions to help design and develop better and safer drug candidates. You will be joining the Computational Chemistry team of Computational and Data Sciences, which closely works with data scientists, computational biologists, and wet-lab colleagues - chemists and biologists.

Our primary focus is improving safety, efficiency and delivery speed for drug candidates using high-dimensional biological data on a cellular level (transcriptomics and high content imaging). You will be in an early group of pioneers developing the world's first AI platform that unveils the causes of emergent disease based on cellular understanding.

This is an exciting opportunity for you to work with proprietary and relevant data sets while learning from some of the best scientists in this realm.  Ideally, we are looking for machine learning experts with experience in the life sciences.  However, if you have an interest in transforming your career from a more classical ML background to machine learning for life sciences, we would love to speak with you. 

Key Responsibilities:

• Enabling and supporting cloud-based machine learning pipelines for predicting the properties of small molecules and improving the models upon rapid feedback from the wet lab experiments.
• Close collaboration with experimental scientists from various teams to ensure that data is being fully utilized and interrogated to deliver high value readouts.
• Presenting results in an interdisciplinary team of biologists, chemists, drug developers, technologists and other machine learning colleagues at company meetings and strategic program readouts
• Define focus on specific project for other team members and/or outsourced personal for machine learning driven research and applied tasks
• Advancing and/or translating machine learning techniques for company development strategy for machine learning both on algorithmic and data source sides

Minimum Qualifications:

• Ph.D. or Master's degree in life or data sciences or related field
• Minimum of 5+ years’ practical experience in Machine Learning model development, especially in neural networks, uncertainty estimation, graph neural network and related fields
• A drive to innovate, an interest in exploring and leveraging new data modalities, and working across interdisciplinary teams
• Advanced programming skills (Python, Julia or related)
• Track record of code contribution with relevant repository or relevant cases showing application of the machine learning in case if code sharing is prohibited by IP
• Fast learner, analytical thinker, creative, "hands-on", strong communication skills.
• Able to work both independently and as part of a team.
• Scientific understanding of molecular and systems biology, diverse molecular data types and analysis tools is plys.
• We would like to see your GitHub repository or papers that can show case this. If you are from biotech/pharma, we would ask you share (where you can), your experiences with a focus on your role and what you specifically contributed to in a program.

Bonus:

• Experience with emergent behavior in complex systems, time series analysis, causal inference, domain adaptation, transfer learning, multi-modal deep learning, geometric deep learning (learning on graphs and/or manifolds)
• Interested in learning any of the above

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.

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.