Machine Learning Engineer

at  Pivotal

ABOUT US:

Pivotal Life Sciences (PLS), part of Nan Fung Group, is a global investment platform focused on life sciences. Leveraging our strong capital base and long-term commitment, we partner with scientists, entrepreneurs, corporations, and investors to advance the life science industry. Our AI team is building the best-in-class data intelligence platform supporting all steps of the venture capital investment process, from deal sourcing to diligence and portfolio value creation. Ultimately, PLS strives to be a scientifically and data driven investor across the life science startup ecosystem. Learn more at www.pivotallifesciences.com

QUALIFICATIONS:

• Bachelor’s degree in Computer Science, Machine Learning, AI, or a related field; Master’s or PhD preferred.
• 5+ years of relevant experience in machine learning and AI, ideally in an ML engineering or MLOps role.
• Strong proficiency in Python.
• Deep understanding of machine learning algorithms and principles, with the ability to implement them in production environments.
• Experience with recent large language models (e.g., GPT-4o, LLama3, Claude) and adjusting LLM model weights through fine-tuning.
• Experience working with vector databases such as pgvector, ChromaDB, etc.
• Experience with AI platforms such as SageMaker, AWS Foundational Models, Hugging Face, etc.
• Proven experience architecting cloud infrastructures on Amazon Web Services (AWS).
• Familiarity with ML workflows and pipelines, and experience with orchestration systems such as Airflow, Metaflow, Prefect, or similar.
• Proficiency in building machine/deep learning models using frameworks like PyTorch, TensorFlow, Keras, or Scikit-learn.
• Knowledge of relational database architecture and data management; SQL expertise preferred.
• Familiarity with software development practices such as unit testing, code reviews, and version control.
• Excellent analytical and communication skills.
• Proficiency in English.

ADDITIONAL REQUIREMENTS:

• Ability to work independently and collaboratively in a fast-paced environment.
• Must have US work authorization; we are unable to sponsor visas at this time.
• Hybrid work schedule: Able to be in the San Francisco office at least 3 days per week (Monday, Wednesday, Thursday), with the option to work from home 2 days per week.

THE ROLE: ML ENGINEER

We are seeking an experienced ML / software engineer with expertise in Machine Learning, MLOps, and Generative AI to join our Data Intelligence team. In this role, you will work alongside data science, data infrastructure, computational biology, and venture investment teams to build and maintain state-of-the-art ML models, generative AI systems, and MLOps pipelines build a best-in-class AI system for investment decision-making in the biotech venture capital space. These AI systems function across all aspects of the biotech venture lifecycle, such as company sourcing, due diligence, portfolio value creation, disease mapping, clinical trial success prediction, and more. This is a great opportunity to work on a range of high impact, high visibility AI projects in a growing team, with exposure to the best life science companies today.