Tessera Therapeutics

Machine Learning Engineer

Cambridge, MA
Machine Learning Deep Learning Python Git Shell
Description

About us

Flagship Pioneering is a biotechnology company that invents and builds platform companies that change the world. We bring together the greatest scientific minds with entrepreneurial company builders and assemble the capital to allow them to take courageous leaps. Those big leaps in human health and sustainability exponentially accelerate scientific progress in areas ranging from cancer detection and treatment to nature-positive agriculture.   

 What sets Flagship apart is our ability to advance biotechnology by uniting life science innovation, company creation, and capital investment under one roof in a way that is largely without precedent. Our scientific founders, entrepreneurial leaders, and professional capital managers are each aligned around an institutionalized process that enables us to innovate and transform for the benefit of people and planet.   

Many of the companies Flagship has founded have addressed humanity’s most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture.  

Flagship has been recognized twice 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, and has been twice named to Fast Company’s annual list of the World’s Most Innovative Companies. 

Pioneering Intelligence (PI) is an initiative focused on AI/ML based scientific innovation within Flagship.  Within PI, our Labs group builds new and experimental AI/ML models with the goal of creating platforms that can accelerate scientific discovery.  We are a team of machine learning scientists and engineers working within an ecosystem of domain experts and entrepreneurs.  We tackle foundational ML challenges and apply those solutions to address core problems in life sciences and beyond.

Project Snapshot: AI Biologist

What if we could build an AI Biologist with:

  • Near-human reasoning over scientific knowledge
  • Super-human ability to process and integrate multiple data modalities
  • Super-human ability to run and interpret virtual (in silico) experiments

We are building on emergent capabilities of foundation models such as multi-step reasoning (LLMs), multi-modal data integration (aligned latents), and few-shot physical property prediction (protein foundation models). Some of our efforts in this space include:

  • Building lifelong-learning systems comprised of foundation models and rich feedback mechanisms, tasked with solving complex scientific problems
  • Improving the underlying biological foundation models, with a specific focus on the kinds of heterogenous, multimodal data omnipresent in biology

The ML Scientist Role

As part of the PI Labs team, ML Scientists will contribute to our ML research projects.  This will involve the ownership of scientific projects within the broader project scope, ranging from conception to execution.

Key responsibilities

Our teams are designed with tight integration between ML Scientists and Engineers, working together to solve problems. Scientists are responsible for:

  • Conceiving of and conducting novel ML research, motivated by scientific milestones important to our team
  • Collaborating with colleagues across Flagship to apply our research to proprietary biological data and processes
  • Working with our ML Engineers to scale and interpret experiments

Requirements

  • PhD in Machine Learning, Computer Science, Statistics, Math, or other related fields.
  • Experience in deep learning research. In particular, significant experience with representation learning, large language models, reasoning systems, or biological foundation models
  • Experience with efficient prototyping, designing experiments, and planning research projects.
  • Fluency in Python and standard ML tools and packages.
  • Strong publication record.
  • Motivated and team oriented, with an ability to thrive in a multidisciplinary environment.
  • Excellent communication and presentation skills. Must be able to think independently and work collaboratively.

Preferred experience

  • Familiarity with common software development tools: Git, cloud/cluster computing, UNIX environments, shell scripting.
  • Experience working on deep scientific problems with a multidisciplinary group

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.

At Flagship, we recognize there is no perfect candidate. If you have some of the experience listed above but not all, please apply anyway. Experience comes in many forms, skills are transferable, and passion goes a long way. We are dedicated to building diverse and inclusive teams and look forward to learning more about your unique background.

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.*

There are more than 50,000 engineering jobs:

Subscribe to membership and unlock all jobs

Engineering Jobs

50,000+ jobs from 4,500+ well-funded companies

Updated Daily

New jobs are added every day as companies post them

Refined Search

Use filters like skill, location, etc to narrow results

Become a member

🥳🥳🥳 216 happy customers and counting...

Overall, over 80% of customers chose to renew their subscriptions after the initial sign-up.

Cancel anytime / Money-back guarantee

Wall of love from fellow engineers