Machine Learning Software Engineer at Flagship Pioneering, Inc.

Cambridge, Massachusetts, United States -

Full Time

Start Date

Immediate

Expiry Date

12 Mar, 26

Salary

156750.0

Posted On

12 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Software Engineering, Uncertainty Quantification, Active Learning, Bayesian Optimization, Drug Delivery, Materials Science, ML Frameworks, Python, MLOps, Cloud Computing, Data Pipelines, Computational Tools, Collaboration, Technical Communication, Problem Solving

Industry

Biotechnology Research

Description

COMPANY DESCRIPTION Mirai Bio, Inc is a Flagship backed, privately held biotechnology company on a mission to transform the current approach to information molecule therapeutics to unlock their full therapeutic potential. In recent years, we have begun to experience the power of information molecules in treating historically undruggable diseases and in designing therapies with unprecedented turnaround times. Mirai’s platform integrates nanoparticle development with world-class informatics technologies and a novel pipeline of experimentation and discovery to drive a new generation of highly effective, therapeutically relevant information molecule therapies. We are seeking collaborative, relentless problem solvers that share our passion for impact to join us! Mirai was founded by Flagship Pioneering. 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 (NASDAQ: SANA). The Role Mirai Bio is seeking a highly talented individual to design, implement, and deploy novel ML approaches to optimize in vivo therapeutic delivery vehicles. They will work cross-functionally to build the computational tools necessary to identify and test therapeutic candidates to enable Mirai’s next generation genomic medicines. The successful candidate will engineer scalable ML platforms and pipelines to overcome limitations of current nucleic acid delivery approaches and will have a strong understanding of targeted information molecule delivery. A successful candidate will have strong familiarity with production-grade ML systems, active learning, and experience working with chemoinformatic libraries. The candidate will also be expected to collaborate extensively with experimental and infrastructure teams. Key Responsibilities Design, build, and deploy production-grade ML models for optimization of lipid nanoparticle (LNP) formulation, synthesis, and in vivo performance. Develop and implement scalable software best practices for uncertainty quantification, ensuring models are reliable for real-time decision-making. Engineer robust data pipelines to integrate multi-fidelity datasets (in silico and in vivo) to accelerate data-driven discovery of novel LNPs Collaborate with computational scientists to translate research models into maintainable, efficient software that identifies design pathways for LNPs that achieve targeted functional properties Work with infrastructure and automation teams to architect and streamline real-time data transfer between predictive models and experimental platforms Partner with experimental teams to drive iterative design–make–test–analyze (DMTA) cycles Communicate findings to stakeholders and leadership through written reports and technical presentations. Professional Experience & Qualifications PhD or Master's in Computer Science, Applied Mathematics, Bioengineering, Chemical Engineering, or a related quantitative field with a strong ML and Software Engineering focus. 4+ years of experience developing and deploying ML models in a production environment within industry and/or academic settings. Strong experience with uncertainty quantification, active learning, and Bayesian Optimization in drug delivery, materials science, or related fields. Proficiency in ML frameworks (PyTorch/TensorFlow/JAX) and the Python data science ecosystem. Demonstrated experience with MLOps principles (version control, CI/CD, monitoring) and hands-on experience with cloud computing infrastructure (e.g., AWS, GCP, Azure) to accelerate model training, deployment, and inference. Strong independent problem-solving ability and attention to detail. Demonstrated achievement in industry or academia (publications, patents, or successful ML system deployments). Excellent communication and presentation skills for both technical and interdisciplinary audiences. Enthusiasm for working with cross-functional teams of experimentalists, engineers, and computational scientists in a fast-paced, entrepreneurial environment. Preferred Qualifications Hands-on experience building and managing ML packages. Experience with ML experiment tracking platforms (e.g. MLflow, Weights & Biases) Familiarity with API development and microservices for integrating ML models into experimental workflows. Background in drug delivery, lipid chemistry, or nanoparticle formulation. ABOUT FLAGSHIP PIONEERING Flagship Pioneering invents and builds platform companies, each with the potential for multiple products that transform human health, sustainability and beyond. Since its launch in 2000, Flagship has originated more than 100 companies. Many of these companies 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 www.flagshippioneering.com. At Flagship, we accept impossible missions to enable bigger leaps. Our core values guide us through uncertainty and toward lasting impact. We are an equal opportunity employer. All qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. We recognize that great candidates often bring unique strengths without fulfilling every qualification. If you have some of the experience listed above but not all, please apply anyway. We are dedicated to building diverse and inclusive teams and look forward to learning more about your background and interest in Flagship. 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. #LI-LD1 The salary range for this role is $96,000 - $156,750. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. Mirai Bio currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on Mirai Bio's good faith estimate as of the date of publication and may be modified in the future.

Responsibilities

The role involves designing, implementing, and deploying ML approaches to optimize therapeutic delivery vehicles. The candidate will collaborate with various teams to build computational tools and data pipelines for drug discovery.