Full-Time Senior Machine Learning Engineer

Paradigm is rebuilding the clinical research ecosystem by enabling equitable access to trials for all patients. Our platform enhances trial efficiency and reduces the barriers to participation for healthcare providers.

Responsibilities:

1. Lead the development, testing, and deployment of ML models and pipelines, with a focus on scalability and integration into production systems.
2. Design and refine GenAI/LLM-based models to streamline and automate clinical trial operations, from data gathering to real-time performance monitoring.
3. Partner with clinicians, informaticists, data scientists, and engineers to build solutions aligned with Paradigm’s mission and goals.
4. Drive improvements in model deployment infrastructure, develop monitoring tools, and refine model performance to ensure robust production-level reliability.
5. Mentor junior ML engineers, contributing to team knowledge-sharing and establishing best practices for data science and machine learning.
6. 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:

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

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