Machine Learning Scientist, Hit Optimization

Company Summary: Founded in 2017 within Flagship Labs, Cellarity’s new approach to drug discovery is based on the computational modeling of cell behavior, leading to a more complete understanding of system and network biology to uncover cell-behavior-targeted medicines for a wide variety of diseases. Cellarity recently raised $123 million in Series B financing. The round included contributions from funds and accounts managed by BlackRock, The Baupost Group, Banque Pictet on behalf of their clients and eight other investors alongside Flagship Pioneering.

Cellarity is generating unprecedented biological insights by combining its unique expertise in network biology, high-resolution data, and machine learning. The result is a new understanding of the cell’s trajectory from health to disease, and how cells relate to one another in tissues. Because the cell and its network of transcripts and proteins offer a more complete view of the complexity of human biology than any individual molecular target, Cellarity’s approach allows for more efficient drug discovery and is designed to drive higher rates of clinical success. Already, the company has seven drug discovery programs underway in diverse therapeutic areas that range from metabolic disease to immuno-oncology.

The successful Series B financing round validates the strength of Cellarity’s science and its potential to redefine drug discovery through its cell-centric approach.

What if you could join a rapidly growing company and play a critical role in bringing new medicines to patients through looking at and treating disease in a revolutionary way.

What this position is all about: Cellarity is seeking a highly motivated and innovative Machine Learning Scientist in the field of computational chemistry with expertise in machine learning for small molecule design to play a vital role in the company’s efforts to validate novel discovery approaches based on cell behavior. The candidate will be responsible for establishing robust molecule design methods and design novel molecules in close collaboration with Machine Learning (ML) and Biology teams, to therapeutically manipulate healthy and diseased cell states and rapidly advance discovery programs within our discovery portfolio. They will be comfortable working in and contributing to a very dynamic and cross-functional team environment. The ideal candidate must be independent, results oriented, with excellent communication skills and be willing to work in a highly dynamic and fast-paced entrepreneurial environment.

What you would be responsible for:

•  Develop and improve machine learning methods to design and optimize novel molecules against targets or other representations.
• Perform analysis of screening results, data mining of internal and external databases to identify new Hits.
• Develop high quality, production ready code with well documented and testable APIs.
• Working in a collaborative CI/CD software development environment, including use of git, participating in code reviews and independent development of robust code.
• Advancing and/or translating machine learning techniques for company development strategy for machine learning both on algorithmic and data source sides.
• Close collaboration with experimental scientists from various teams to ensure that data is being fully utilized and interrogated to deliver high value readouts.
• Demonstrated ability to successfully work in cross-functional teams with an emphasis on teamwork, collaboration, and communication within team and across the department.

What experiences will you need:

• D. or Master's degree in life or data sciences or related field.
• Experience with at least one of the cheminformatics toolkits (OpenEye/RDKit/Schrodinger suite, etc) is a plus.
• Expertise with at least one modern machine learning framework (Pytorch, TensorFlow, Keras).
• Minimum of 3 years practical experience in Machine Learning model development, especially in neural networks, uncertainty estimation, model benchmarking, graph neural network and related fields.
• Demonstrated ability to develop novel machine learning methods that go beyond putting together of existing code, and to apply problem-solving skills to complex issues.
• Advanced programming skills (Python, Julia or related).
• Scientific understanding of molecular and systems biology, diverse molecular data types and analysis tools is plus.

What sets you apart:

• 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).
• Experience in computational chemistry, QSAR models, generative models and/or ligand based drug discovery is a plus.
• Experience or understanding of the drug discovery process.
• Innovative problem-solver, with a track record of impacting drug project delivery.
• Interested in learning any of the above.

What it’s like to work at Cellarity
At Cellarity, we

1. Push Boundaries: We create a legacy with breakthrough science in the service of patients.
2. Act with urgency: We work quickly and with conviction, and are eager to learn from data to iterate.
3. Own it: We transcend our job descriptions and relentlessly follow through on our commitments.
4. Tell it like it is: We give regular feedback on behaviors and are accountable for how we treat people.
5. Energize others: We are easy to work with and build strength from differing perspectives.

Cellarity 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.

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