FL84: Data Engineer, Machine Learning Ops

Company Summary:

Each day, the lives of more than 2 billion people across the globe are impacted by chronic diseases. Moreover, the economic burden on society of treating chronic disease is spinning out of control. Today, this dire situation appears unlikely to change as >95% of global healthcare costs are spent on treating rather than preventing chronic diseases. FL84, Inc. is a privately held early-stage company that is applying advanced biological and computational platforms to discover breakthroughs in detection of and intervention against the etiologies that drive progression from health to disease. Our goal is to leverage our proprietary platforms to disrupt the current approach of treating chronic disease too late. We endeavor to provide true health care rather than sick care to individuals that are at risk of progressing to disease.

FL84 was founded by Flagship Pioneering, an innovation enterprise dedicated to originating and developing first-in-category life sciences companies. Flagship Pioneering conceives, creates, resources, and develops first-in-category life sciences companies to transform human health and sustainability. Since its launch in 2000, the firm has applied a unique hypothesis-driven innovation process to originate and foster more than 100 scientific ventures, resulting in over $30 billion in aggregate value. The current Flagship ecosystem comprises 37 transformative companies, including: Moderna Therapeutics (NASDAQ: MRNA), Rubius Therapeutics (NASDAQ: RUBY), Indigo Agriculture, and Sana Biotechnology.

Position Summary:

We are seeking a creative and motivated MLOps Data Engineer to help us build a machine learning platform capable of disambiguating the mysteries of chronic disease progression. As a member of a larger data science group, she/he/they will work across the stack to develop, test, deploy, and maintain ML based solutions. The successful candidate will work closely with ML scientists, Computational Biologists, and Informatics/IT engineers to implement a scalable platform that rapidly advances our scientific programs. 

The role may also include significant hands-on analyses of clinical data such as electronic health records, insurance claims, laboratory measurements, images, free text, and genetic data. The candidate will work closely with the data science and computational biology teams to accelerate and create insights and novel prediction platforms for different stages of the journey from health to disease.  The position will provide a unique opportunity to play a foundational role in the development of FL84’s preclinical platform and explore the complexities of disease progression.

Key Responsibilities:

• Design, develop and refine infrastructure for FL84’s ML platform, enabling rapid model development, training, evaluation at scale
• Deploy and monitor cutting-edge ML models and algorithms developed by ML team
• Implement large-scale MLOps and data ETL pipelines
• Develop solutions for efficiently performing ML model experimentation and tuning
• Establish data engineering processes and best-practices for data scientists utilizing our ML platform and storage of underlying data
• Cultivate a data-centric and process-oriented company philosophy by helping to maintain best practices for software development, data management, and infrastructure
• Monitor and evaluate new and emerging technologies and models and identify opportunities for collaboration within Flagship Pioneering companies, academia, and third parties

Basic Requirements:

• 3+ year’s experience working in a DevOps or data engineer role using AWS cloud-based infrastructure
• Proficiency in Python and strong object-oriented design skills coupled with a solid understanding of data structures and algorithms
• Familiarity with implementing large-scale data ETL pipelines or container orchestration tools in a production setting
• Demonstrated self-motivation and willingness to dive into complicated data engineering challenges
• Experience in Big Data / Spark / Hadoop development
• Ability to work in a fast-paced environment and strong technical communication skills

Preferred Requirements:

• AWS credentials or equivalent experience
• Familiar with multiple of the following areas/topics: regression models, regularization, recurrent neural networks, graph neural networks, LSTMs, or CNNs
• Experience working with reference genetic and other biological databases and datasets (e.g., UK Biobank, TCGA, CMAP, LINCS) is a strong plus
• Ability to Google error messages and seek resolution from self-investigation

Flagship Pioneering 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: 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.