(Senior) Machine Learning Engineer, Bayesian Optimization

Company overview:

Flagship Labs 109, Inc. (FL109) is a privately held, early-stage technology company pioneering the use of artificial intelligence, physics and hardware to transform the way we see biology. FL109 was conceived by Flagship Pioneering, which brings the courage, long-term vision, and resources needed to realize unreasonable results. Become part of our mission-driven team and help envision the future of science.

Overview:
We are seeking a ( Senior) Machine Learning Engineer with deep expertise in Bayesian optimization , protein design , and generative modeling to help lead the development of next-generation AI systems in the protein space. This role will focus on solving state-of-the-art problems structural biology and protein design. You will collaborate closely with a multidisciplinary team of scientists to push the boundaries of biological understanding and generative protein modeling, with opportunities to mentor others while translating research into production-ready tools, experimental designs, and powerful new datasets.

Key Responsibilities:

• Apply Bayesian optimization and other active learning techniques to diverse problems.


• Develop, train, and fine-tune generative models (ex: diffusion models, transformers) for encoding and designing protein structures and sequences.


• Collaborate with diverse functions (ex: structural biologists, protein engineers) to incorporate physical, structural, or biological priors into the model.


• Deliver models and insights to guide experimental design and data generation.


• Mentor junior engineers and contribute to the direction of the ML engineering function.


• Track and present model performance, research progress, and infrastructure improvements to internal stakeholders.

Required Qualifications:

• PhD or MSc in Computer Science, Machine Learning, Computational Biology, Biophysics, or a related field.


• 2+ years of experience in developing and deploying machine learning models in industry or applied research settings.


• Strong background in Bayesian optimization , active learning , or experimental design for high-dimensional biological problems .


• Experience with large-scale generative models (ex: diffusion models, transformers) and distributed training (multi-GPU, multi-node).


• Proficiency in Python and modern ML frameworks such as PyTorch or TensorFlow.


• Hands-on experience with ML infrastructure, including cloud services (AWS, or Azure) and container orchestration (Kubernetes, Docker).

About Flagship

Flagship Pioneering is a bioplatform innovation company that invents and builds platform companies, each with the potential for multiple products that transform human health or sustainability. Since its launch in 2000, Flagship has originated and fostered more than 100 scientific ventures, resulting in generation of over 500 patents, initiation of over 50 clinical trials for novel therapeutic agents and an aggregate value of more than $90 billion. 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. Learn more about Flagship at .

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.

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.