Senior Machine Learning Engineer

Role Description

By joining our team as a Senior Machine Learning Engineer, you will play a pivotal role in building cutting-edge AI products that directly impact how new therapies reach patients. We’re looking for an experienced ML engineer who is passionate about turning advanced AI research into scalable, real-world solutions. You thrive on solving complex problems, pay close attention to detail, and consistently seek to automate and improve processes. You shine as a collaborator and excel as an individual contributor, with the courage to tackle challenging problems and the humility to learn and adapt. Your initiative and discipline allow you to thrive while working remotely, and your high degree of empathy and communication skills makes you the kind of colleague everyone wants on their team. As an integral member of our fast-growing organization, you will leverage AI to transform clinical research and improve patient care.

What You’ll Be Working On:

• Build and deploy AI-driven products that accelerate clinical trials and improve patient outcomes.
• Develop advanced ML models and LLM-powered agents for critical use cases like patient recruitment, enrollment forecasting, and study feasibility.
• Leverage modern cloud tools and MLOps best practices to build robust data pipelines and deploy models at scale.
• Collaborate across teams of data scientists, product managers, designers, engineers, and domain experts to integrate AI capabilities into our platform.
• Continuously learn and innovate, staying up-to-date with the latest developments in ML/AI.

Qualifications

• Minimum of 5+ years of hands-on experience building and deploying machine learning solutions in production at scale.
• Proficiency in Python and its ML ecosystem (pandas, scikit-learn, TensorFlow/PyTorch).
• Experience with functional programming (e.g. Clojure) is a plus but not required.
• Experience with modern cloud infrastructure (AWS or similar) and containerization tools like Docker.
• Strong understanding of machine learning fundamentals and statistical modeling.
• Familiarity with NLP and large language models is important.
• Ability to break down complex problems and devise effective, efficient ML solutions.
• A passion for our mission to speed up clinical trials and improve patient outcomes.

Requirements

• Proven ability to implement end-to-end ML pipelines from data ingestion to model serving for real-world applications.
• Comfortable working with large datasets, writing complex SQL queries, and leveraging modern data processing frameworks.
• Familiarity with MLOps best practices such as CI/CD pipelines, automated testing, and monitoring model performance/data drift.
• Balance pragmatic engineering with scientific rigor, ensuring models are accurate, performant, and maintainable in production.

Benefits

• The expected pay range for this role is $140,000 - $190,000 USD per year for full-time team members.