Machine Learning Engineer
Cambridge, MA USA
Flagship Pioneering, Inc.
We are Flagship Pioneering We are a biotechnology company that invents platforms and builds companies that change the world. Pioneering Partnerships…The Company
FL100, Inc. is a privately held, early-stage company pioneering the use of artificial intelligence-based agents to build an integrated, end-to-end platform for AI-driven product innovation. FL100 has created intelligent and reliable AI agent-powered workflows for emergent product innovation. Emergent product innovation leads to new products with breakthrough market adoption that generate new sources of value by solving for large unmet consumer needs and creating demand that did not exist previously.
We're leveraging multi-agent systems to accelerate growth, speed up product design innovation, and automate e-commerce operations. Our vision is to create a multi-platform service that empowers anyone to build and operate an e-commerce business efficiently. Currently, we offer a Shopify app that demonstrates our capabilities, with plans to expand across various e-commerce platforms and online marketplace.
FL100 is backed by Flagship Pioneering, an innovation enterprise that conceives, creates, resources, and builds companies that invent breakthrough technologies to transform health care, agriculture, and sustainability. Flagship has created over 100 groundbreaking companies since 2000, including Moderna.
The Role
We’re seeking a Machine Learning Engineer to develop and operationalize advanced AI solutions for our multi-agent e-commerce automation platform. You will design and implement end-to-end ML workflows—encompassing data pipelines, model training, and production deployment. This hands-on role requires strong collaboration with AI/ML researchers, software engineers, and product managers to create impactful, AI-driven products that integrate seamlessly with e-commerce platforms and online marketplaces (e.g., Shopify, Amazon, eBay).
Key Responsibilities
- Design and implement end-to-end ML pipelines, from data ingestion and feature engineering to model deployment.
- Collaborate with cross-functional teams (AI researchers, backend developers, product managers) to build production-ready AI services and APIs.
- Develop and maintain scalable model serving infrastructure (e.g., using Docker, Kubernetes, FastAPI, or Flask).
- Integrate ML models with various e-commerce (Shopify, WooCommerce) and online marketplace (Amazon, eBay) data sources to enable seamless, real-time decision-making.
- Implement CI/CD processes and automated testing for rapid experimentation, A/B testing, and model releases.
- Monitor and troubleshoot model performance and reliability, proactively detecting drift or anomalies and implementing improvements.
- Optimize data pipelines and model architectures for speed, scalability, and cost-efficiency in a cloud-native environment.
- Stay current with emerging ML/AI trends and technologies, driving continuous improvement and innovation in our platform.
Qualifications
- 3+ years of hands-on experience in machine learning engineering or related roles.
- Proficiency in Python and popular ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn).
- Demonstrated ability to serve ML models at scale (e.g., Docker, Kubernetes, AWS Sagemaker, or equivalent MLOps tools).
- Strong grasp of data engineering practices, including ETL pipelines, data validation, and feature engineering.
- Familiarity with cloud services, preferably AWS (S3, EC2, ECR, Lambda, ECS/Fargate).
- Experience with CI/CD pipelines (GitHub Actions, Jenkins, CircleCI, or equivalent).
- Excellent collaboration skills and comfort working in a fast-paced environment.
- Problem-solving mindset and ability to communicate complex ideas effectively.
Preferred Qualifications
- Experience with LLMs or Agentic systems.
- MLOps expertise using tools such as MLflow or Kubeflow.
- Familiarity with e-commerce or online marketplace API integrations (Shopify, WooCommerce, Amazon, eBay).
- Advanced degree (MSc or PhD) in Computer Science, AI, or related field.
- Knowledge of serverless architectures and microservices.
- AWS certifications (e.g., Machine Learning Specialty, Solutions Architect).
- Exposure to big data technologies (Spark, Hadoop) for large-scale data processing.
- Front-end or full-stack experience (React, Node.js) for quick prototyping.
Values and Behaviors
- Constant Learner: Seeks out emerging ML/AI trends and harnesses them for practical impact.
- Customer-Obsessed: Designs solutions that deliver real value to users, keeping the customer’s needs at the forefront.
- Mission-Oriented: Committed to bringing breakthrough AI technologies to market.
- Entrepreneurial Spirit: Embraces ambiguity and drives innovative solutions independently.
- Works with Velocity & Urgency: Efficiently tackles challenges with a results-driven approach.
- Collaborative: Partners effectively with cross-functional teams and stakeholders.
- Accountable: Maintains ownership of initiatives and delivers on commitments.
- Growth Mindset: Views experimentation and iteration as opportunities for improvement.
- Innovative: Thinks outside the box to advance AI-driven product innovation.
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.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: A/B testing APIs Architecture AWS Big Data CI/CD Computer Science Data pipelines Docker EC2 E-commerce ECS Engineering ETL FastAPI Feature engineering Flask GitHub Hadoop Jenkins Kubeflow Kubernetes Lambda LLMs Machine Learning Microservices MLFlow ML models MLOps Model deployment Model training Node.js PhD Pipelines Prototyping Python PyTorch React SageMaker Scikit-learn Spark TensorFlow Testing
Perks/benefits: Career development Startup environment Team events
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