Engineering Manager, Machine Learning

We are looking for a Engineering Manager, Machine Learning to join our team. In this role, you will lead a team of data scientists to build and integrate advanced machine learning models, including NLP and LLM-based models, that streamline clinical trial execution activities. You will play a crucial role in designing data-driven solutions to improve trial design, patient recruitment, and overall trial efficiency. Your work will directly contribute to speeding up the clinical trial process and bringing life-saving treatments to patients faster.

What You'll Do:

• Lead and mentor a team of data scientists in developing, productionizing, and monitoring ML models at scale.
• Oversee the design and deployment of algorithms, including GenAI/LLM-based models, to support trial execution activities.
• Collaborate closely with cross-functional teams, including clinicians, informaticists, engineers, and stakeholders, to align data science initiatives with business goals.
• Guide the team through the process of gathering requirements, defining model specifications, and generating training and validation datasets.
• Lead the integration of ML models into production infrastructure, collaborating with engineering teams to ensure seamless execution.
• Drive innovation in data science practices and establish a long-term technical vision for the team.
• Communicate the technical and business value of data science initiatives to both technical and non-technical audiences.
• Promote best practices in data science, ensuring high-quality code and model development through effective reviews and mentoring.

Who You Are:

• PhD or Master’s in data science, statistics, computer science, or a related field.
• 7+ years of experience in data science or a related field, with a focus on healthcare or adjacent industries.
• 2+ years of leadership experience, with proven ability to lead data science teams and set technical direction.
• Strong experience in machine learning, including model training, evaluation, and deployment.
• Hands-on experience with Python, and deep knowledge of machine learning algorithms and statistical methods.
• Experience managing production-level data science infrastructure, including pipelines, deployment, and monitoring.
• Excellent problem-solving and strategic thinking skills, with the ability to tackle complex business and technical challenges.
• Comfortable working in a mission-driven, fast-paced startup environment with high ambiguity.

Bonus:

• Experience with oncology and/or clinical trial data.
• Experience with GenAI/LLM-based model development and open-source frameworks for building LLM applications.
• Previous experience in an early-stage startup environment and enthusiasm for high-growth, dynamic, 0-1 projects.

The base compensation range is $200,000 – $230,000 USD per year. Actual salaries will vary based on candidates' qualifications, skills, and location.