(Senior) Machine Learning Engineer at Flagship Pioneering, Inc.

Cambridge, Massachusetts, United States -

Full Time

Start Date

Immediate

Expiry Date

12 Jun, 26

Salary

215000.0

Posted On

14 Mar, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, AI Solutions, ML Pipelines, LLM Integration, Model Deployment, PyTorch, Python, Software Engineering, Git, CI/CD, Cloud Computing, AWS, Distributed Training, Computer Vision, Performance Optimization, Scalability

Industry

Biotechnology Research

Description

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. The Role: FL109 is seeking a talented Machine Learning Engineer to support the creation and deployment of state-of-the-art AI solutions to transform how we see molecular biology. You are passionate about solving real-world problems, thrive on shipping impactful solutions, and enjoy working in a dynamic startup environment. Your role will focus on implementing robust ML pipelines, optimizing models for production, and collaborating across teams to turn innovative ideas into scalable products. How You Will Contribute: Pipeline Development: Build and optimize end-to-end ML pipelines, including data preprocessing, model training, validation, and deployment. Ensure solutions are robust, scalable, and efficient. LLM Integration: Implement and fine-tune large language models for various applications, ensuring their effective integration into existing pipelines and workflows. Model Deployment: Develop production-grade ML systems that integrate seamlessly with experimental workflows. Focus on creating systems that are both reliable and impactful in real-world applications. Collaboration: Partner with ML researchers, experimentalists, and other team members to implement solutions aligned with scientific and business objectives. Code Implementation: Write clean, maintainable, and efficient code to support the design and deployment of AI tools. Performance Optimization: Implement strategies to improve computational performance and efficiency, including working with cloud-based environments and distributed systems. Scalability: Work closely with the infrastructure team to ensure AI solutions scale effectively with increasing data and computational demands. The Ideal Candidate Will Have: Hands-on experience with shipping production-grade ML systems, including expertise in deployment, monitoring, and optimization. Experience with large language models (LLMs), including fine-tuning, inference optimization, and application development. Proficiency in Python and ML frameworks such as PyTorch. Strong understanding of software engineering principles, version control (e.g., Git), and CI/CD pipelines. Familiarity with cloud computing platforms (e.g., AWS) and distributed training of ML models. A background in computer vision or experience working with noisy, unstructured data is a plus. Excellent problem-solving skills and the ability to work both independently and collaboratively in a fast-paced environment. Passion for contributing to impactful projects at the intersection of AI and cutting-edge science. 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 www.flagshippioneering.com. 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. The salary range for this role is $132,000 - $215,000. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. FL109 currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on FL109's good faith estimate as of the date of publication and may be modified in the future.

Responsibilities

The role focuses on building and optimizing end-to-end Machine Learning pipelines, including data preprocessing, model training, validation, and deployment, while also implementing and fine-tuning large language models for various applications. Responsibilities include developing production-grade ML systems that integrate with experimental workflows and collaborating with researchers and other team members to achieve scientific and business objectives.