Machine Learning Operations Engineer

At Flagship Pioneering, we conceive, create, resource, and develop first-in-category life sciences companies to transform human health and sustainability. We’ve created over 100 scientific ventures, including the now familiar drug and vaccine innovator, Moderna Therapeutics.

Since its inception in 2000, many of our companies have leveraged advances in computing, big data and AI. In recent years, this trend has accelerated with first-in-category life science companies such as Generate Biomedicines, Cellarity, Valo and many others that are creating breakthrough innovations using AI and ML technologies.

We are looking for extraordinary computational scientists, engineers, and entrepreneurs to work alongside individuals within the Flagship Ecosystem focused on solving the most impactful challenges in AI and the life sciences.

Description

The ML Ops Engineer will help shape the ML pipeline for our research scientists and Associates. They will take ownership of multiple code bases at different levels of production-readiness and contribute to growing the code bases. This is an exciting opportunity to be part of a fast-paced, highly dynamic entrepreneurial environment.

Key Responsibilities:

• Work with an interdisciplinary team of ML scientists, biologists and engineers to build the infrastructure and best practices for novel ML and DL pipelines applied to various biological problems and datasets.
• Work with a team to implement large machine learning models at scale on the cloud.
• Willingness to switch back and forth between a fast-paced prototype-heavy working environment, and a more rigorous production-oriented environment.
• Manage several git repositories, including organizing code merges.
• Ability to design, articulate, and implement best practices in software engineering across multiple projects.
• Monitor and evaluate new and emerging technologies and models, with an eye towards rapid prototyping and eventual integration into the full ML pipeline.

Basic Requirements:

• 2+ years industry experience in ML Ops or equivalent.
• Fluency with AWS, GCP, or similar cloud-computing services.
• Fluency in python and standard ML tools and packages (e.g. PyTorch, PyG,  etc.).
• Experience with containerization and task orchestration tools (e.g. Docker, Kubernetes, Slurm)
• Motivated and team oriented, with an ability to thrive in a multidisciplinary environment.
• Ability to independently plan and implement ML engineering projects, while maintaining close communication with team members.
• Excellent collaboration skills. Must be able to think independently and contribute to an active intellectual environment.

Preferred Requirements:

• Experience with a wide range of DL models (GANs, diffusion models, large language models, etc…), and the intricacies of managing experiments
• Familiarity with ETL pipelines for large datasets, and workflow managers (e.g. AirFlow, Prefect, etc…)
• Experience with data lakes
• Familiarity with full web-stack principles

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.*