Senior Machine Learning Engineer

As a Senior Machine Learning Engineer, you will take a leading role in designing and deploying sophisticated ML models, including GenAI and LLM-based solutions, that optimize clinical trial workflows and patient engagement. This position offers an opportunity to impact healthcare by developing state-of-the-art models that enhance trial design, accelerate patient recruitment, and improve overall trial efficiency. You will contribute to both high-level architecture decisions and hands-on implementation, driving the technology forward and influencing ML strategies across Paradigm.

Responsibilities:

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

Qualifications:

• Education: Master’s or PhD in computer science, statistics, machine learning, or a related field.
• Experience: 5+ years of experience as a machine learning engineer, with a proven track record in healthcare, life sciences, or a related field.
• Technical Skills: 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.
• Production-Level ML Expertise: Experience managing production-level pipelines, including model deployment, monitoring, and continuous integration.
• Problem Solving & Collaboration: Advanced analytical skills and a collaborative approach to solving complex challenges across teams.
• Startup Mindset: Adaptability and experience in fast-paced, mission-driven environments with high levels of ambiguity.

Preferred:

• Healthcare/Clinical Trials Experience: Background in working with oncology or clinical trial data.
• GenAI/LLM Proficiency: Hands-on experience developing and deploying GenAI/LLM-based models and open-source frameworks for LLM applications.
• Startup Experience: Previous involvement in an early-stage startup, ideally in health tech or life sciences, with a passion for high-growth projects.