Senior Machine Learning Engineer

Company Overview

Extuitive is a Flagship Pioneering–backed startup reimagining product innovation for the AI era. Our mission is to empower entrepreneurs and direct-to-consumer (D2C) brands with AI-driven tools that simplify, accelerate, and scale the launch of new products. Based in Cambridge, MA, we operate like a special ops unit—fast-moving, data-driven, and relentlessly focused on impact.

About the Role  

As a Senior Machine Learning Engineer, you’ll be responsible for designing, building, and deploying the ML systems that power our platform. You’ll work across the full lifecycle — from framing problems, experimenting with models, and fine-tuning LLMs, to deploying them in production and monitoring performance. Beyond shipping models, you’ll influence architecture decisions, set ML best practices, and help define how AI shapes our product experience. 

Responsibilities

• Build and Deploy ML Models That Power the Product - Translate product requirements (e.g., “recommend the best product” or “summarize customer feedback”) into ML problems. Select, fine-tune, or train models (LLMs, embeddings, classifiers, recommenders) that deliver real customer value. 
• Own the ML Pipeline End-to-End - Design data pipelines for collection, cleaning, feature engineering, and labeling. Set up lightweight MLOps practices (CI/CD for models, reproducibility, experiment tracking).  
• Make Pragmatic Technical Decisions - Balance off-the-shelf APIs (OpenAI, Anthropic, Hugging Face) vs. custom models, depending on speed, cost, and IP.  
• Wear Multiple Hats - Jump in on DevOps, analytics, or even light backend integration when needed. Help with customer-facing issues (debugging, bug fixes, UI polish) in real time. 

Requirements 

• 5+ years of professional experience in applied machine learning 
• Master of Science degree in ML, Software Engineering, or equivalent  
• Strong background in Python and ML frameworks (PyTorch, Hugging Face, Scikit-learn, Torchtune, Deepspeed or equivalent). 
• Experience with LLMsor recommendation systems in production environments. 
• Strong understanding of data engineering: pipelines, ETL, feature stores. 
• Familiarity with vector databases, embeddings, and real-time inference. 
• Comfort with cloud ML infrastructure (AWS/GCP/Azure) and GPU usage. 
• Experience in MLOps: experiment tracking, model versioning, monitoring. 
• Passion for writing clean, maintainable code and establishing best practices. 
• Comfortable working in a fast-paced startup environment, where priorities evolve quickly. 

More About Flagship Pioneering

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 more than $90 billion in aggregate value. 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 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 tra