Senior AI / ML Engineer

ML/AI Engineer

We’re looking for a driven, hands-on ML/AI Engineer to help us push the boundaries of what's possible in AI-driven drug development. You’ll work on production-grade LLM-based systems, knowledge graphs, and machine learning pipelines—turning prototypes into powerful tools that make a real-world impact.

You'll collaborate across teams to design, build, and deploy intelligent systems that enhance how life sciences organizations make critical decisions. If you love working on technically challenging problems with direct impact in healthcare—this is the role for you.

This is a remote-first position, but we’d love it if you’re based in or near Boston.

What You'll Do:

• Design and Deploy LLM Systems: Develop scalable, production-ready LLM applications using frameworks like LangChain/LangGraph. Build robust RAG pipelines and integrate knowledge graphs for biological and clinical data.
• Full-Stack AI Engineering: Write maintainable, high-performance code and build clean APIs and services for machine learning applications.
• Data Engineering Collaboration: Work with data engineers to build and optimize data workflows and pipelines for high-quality data ingestion and processing.
• Product-Focused Prototyping: Collaborate with product and domain teams to rapidly prototype AI solutions, iterate based on feedback, and scale models for production.
• Model Deployment & MLOps: Use modern MLOps tools to deploy and monitor models in production environments (AWS preferred). Ensure scalability, observability, and resilience.
• Collaborative Innovation: Partner with engineering, data, and business teams to identify and develop high-value AI/ML applications.
• Continuous Learning: Stay ahead of the curve on emerging ML frameworks, GenAI capabilities, and healthcare technologies.

What We’re Looking For:

Core Qualifications:

• Education: Bachelor's, Master’s, or Ph.D. in Computer Science, Data Science, Engineering, or a related field.
• Hands-on AI Experience:
• LLM & LangChain Experience: Practical experience working with frameworks like LangChain for applications such as Q&A systems, chatbots, or document automation.
• Software Engineering: Strong coding skills in Python and experience using Git/GitHub and CI/CD practices.
• Data Engineering Know-how: Comfort working with ETL pipelines, relational and non-relational databases, and data platforms like Snowflake or Databricks.
• Big Data & ML Frameworks: Familiarity with Big Data tools (e.g., Apache Spark) and experience orchestrating data workflows using tools like Apache Airflow.
• Cloud & MLOps: Experience with deploying ML models in cloud environments (AWS, GCP, or Azure) and using containerization/orchestration tools like Docker and Kubernetes.

Soft Skills:

• Strong problem-solving skills and an analytical mindset.
• Passion for continuous learning, rapid prototyping, and iterating based on user needs.
• Autonomous, self-starter attitude with a strong sense of ownership.
• Excellent communication skills—able to explain technical ideas clearly to non-technical audiences.
• Collaborative team player with a desire to build things that truly matter.

Bonus:

• Experience in healthcare, life sciences, or biopharma sectors (preferred but not required).

Why Join Us?

• Make a tangible impact on drug development and patient outcomes.
• Work with a passionate, mission-driven team tackling complex challenges.
• Enjoy flexibility and autonomy in a remote-first culture.
• Competitive salary, equity, and benefits.
• Opportunity to grow with a fast-moving, well-funded startup backed by top-tier investors.

What We Offer

• Impact: Your work directly enables breakthrough therapies to reach patients faster
• Ownership: Build and lead the customer success function as a foundational leader
• Growth: Shape customer experience during a critical scaling phase
• Compensation: Competitive salary, performance bonus, and equity
• Team: Collaborative, mission-driven colleagues passionate about transforming biopharma

Location

We are a remote-first company, but looking for team members to be located in the Northeast (Boston, New York, DC, etc.)