Principal Scientist, Machine Learning

Key Skills

Aartificial intelligence, Design, Effective communication skills, Machine learning techniques, PyTorch, TensorFlow

Job Description

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?

Montai Health is a privately held, early-stage biotechnology company developing a platform for understanding and leveraging complex molecular interactions within organisms to solve global challenges in human health and sustainability. The company leverages a multidisciplinary approach that integrates tools ranging from machine learning and big data to multi-omics and high-throughput screening.

At Montai, we nurture a bold, spirited and leading-edge culture dedicated to strengthening human health:

• We are one team with omnidirectional trust, empowered and accountable
• We are strong as individuals but stronger as a team and we are committed to excellence
• We have a sense of urgency and persistence and we are crazily confident that we can make a difference
• We need to be comfortable with the uncomfortable and be rigorous and we recognize that failure is data
• We care for diversity in people, thought, personality, opinions, background and distinctiveness
• We have a sense of humor to help us manage through our strategic noise

Position Summary

• Independently leads design and implementation of novel biochemical machine learning models for molecular property prediction and other drug development tasks
• Domain expert that identifies novel opportunities to advance drug development practices using ML and determines objectives for major modeling projects
• Drives collaboration cross-functionally across diverse technology and biology teams to build and deploy ML capabilities across multiple drug development programs
• Supports innovation and implementation across diverse modeling efforts among a team of 10+ ML scientists, within and beyond projects they are directly responsible for
• Coordinates collaboration between ML and software engineers to design, adopt, and implement coding, documentation, and deployment best practices for ML models
• Communicate widely with internal stakeholders including biology, chemistry, and clinical functional leads, and externally to scientific communities through advisory conversations and conference presentations
• Upholds high standards of quality, empathy, and support as a collaborative team member and project mentor

This person will work with and contribute to an innovative set of machine learning models and tools built on top of a robust ML engineering infrastructure. They will build valuable experience in...

• Innovation of ML models designed to tackle novel challenges in natural product chemistry and Anthromolecule™ drug development
• Leading practices for ML and software engineering in a ML research environment
• Direct engagement dry lab-wet lab engagement for closed loop biological data generation in iterative and active learning contexts

Required qualifications

• 7+ years applied experience applying computational and machine learning methods in drug development
• PhD in computational or systems biology, computer science, statistics, machine learning, chemistry, physics, or a related field; or equivalent (4+ years) additional applied experience
• Demonstrated expertise in graph convolutional deep neural network modeling
• Highly experienced in python-oriented ML design and development in e.g. pytorch or TensorFlow
• Highly collaborative team member eager to work with experts from multiple domains (biology, chemistry, statistics, ML, software engineering, business strategy)
• Excellent communicator able to convey complex technical ideas across disciplinary boundaries

Recommended experience

• Demonstrated ability to build and deliver ML tools supporting drug development programs
• Experience coordinating development and deployment of in silico tools directly with biology SMEs in a drug development setting
• Experience with 3D convolutional, transformers, and other ML architectures for chemical representation learning.
• Experience with ML applications in molecular property prediction for high throughput screening (HTS) of small molecules, systems biology, and/or structural biology
• Experience with docking, molecular dynamics, and other physics-based simulation tools for small molecule-protein interactions
• Experience with modern DAG-based ML cloud workflow orchaestration tools such as Nextflow, snakemake, Flyte, or redun
• Experience working with large scale in vitro assay, in vivo, clinical, biological pathway, multi-omics, and other biochemical datasets

More About Flagship Pioneering

Flagship Pioneering has conceived of and created companies such as Moderna Therapeutics (NASDAQ: MRNA), Editas Medicine (NASDAQ: EDIT), Omega Therapeutics (NASDAQ: OMGA), Seres Therapeutics (NASDAQ: MCRB), and Indigo Agriculture. Since its launch in 2000, Flagship has applied its unique hypothesis-driven innovation process to originate and foster more than 100 scientific ventures. In 2021, Flagship Pioneering was ranked 12th globally 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.

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.