Senior Machine Learning Engineer

Paradigm is rebuilding the clinical research ecosystem by enabling equitable access to trials for all patients. As a Senior Machine Learning Engineer, you will take a leading role in designing and deploying sophisticated ML models to optimize clinical trial workflows and patient engagement.

Responsibilities:

• Lead the development, testing, and deployment of ML models and pipelines, with a focus on scalability and integration into production systems
• Design and refine GenAI/LLM-based models to streamline and automate clinical trial operations, from data gathering to real-time performance monitoring
• Partner with clinicians, informaticists, data scientists, and engineers to build solutions aligned with Paradigm’s mission and goals
• Drive improvements in model deployment infrastructure, develop monitoring tools, and refine model performance to ensure robust production-level reliability
• Mentor junior ML engineers, contributing to team knowledge-sharing and establishing best practices for data science and machine learning
• Present complex technical insights and results to both technical and non-technical stakeholders, advocating for data science-driven strategies that align with business objectives

Requirements:

• Master's or PhD in computer science, statistics, machine learning, or a related field
• 5+ years of experience as a machine learning engineer, with a proven track record in healthcare, life sciences, or a related field
• Deep expertise in training, fine-tuning, and deploying ML models, including experience with GenAI/LLMs
• Proficiency in Python, SQL, and familiarity with cloud infrastructure and ML engineering best practices
• Experience managing production-level pipelines, including model deployment, monitoring, and continuous integration
• Advanced analytical skills and a collaborative approach to solving complex challenges across teams
• Adaptability and experience in fast-paced, mission-driven environments with high levels of ambiguity
• Background in working with oncology or clinical trial data
• Hands-on experience developing and deploying GenAI/LLM-based models and open-source frameworks for LLM applications
• Previous involvement in an early-stage startup, ideally in health tech or life sciences, with a passion for high-growth projects