Lantern Pharma - Plano, TX
posted about 2 months ago
Lantern Pharma is seeking a talented and highly motivated Lead Data/Infrastructure Engineer to build and enhance our RADR AI platform that can predict drug response, therapeutic benefit, and survival outcome of cancer patients. In this role, you will work directly with our RADR team to take ownership of developing the engineering side of our platform, focusing on creating a robust backend data infrastructure that supports both Lantern's internal AI scientists and external-facing partnerships. This position offers the opportunity to work with cutting-edge data tools and be part of a team at the forefront of AI-driven oncology. The ideal candidate will possess an entrepreneurial mindset, be comfortable with creative problem-solving, and be excited to build engineering infrastructure from the ground up in a flexible, fast-paced environment. You will play a crucial role in the evolution of Lantern's science and platform, providing opportunities for growth and significant impact within the organization. Your contributions will directly influence the development of precision oncology solutions that can transform drug development processes. As a Lead Data/Infrastructure Engineer, you will help set the company's overall engineering strategy and growth, which includes developing technical infrastructure, assessing security, and building the engineering team(s). You will adopt a player/coach mentality, working hands-on to build out data pipelines and infrastructure while also managing a team of engineers to support overall data engineering and infrastructure goals. Your responsibilities will include taking ownership of supporting, architecting, and building a system for efficient data ingress/ETL pipelines for both existing data assets and newly identified data sources. Additionally, you will manage engineering activities with cloud systems (AWS), including data transfers, budget estimates, and engaging with external partners such as cloud providers. You will collaborate with an interdisciplinary team of computational biologists and machine learning scientists across multiple projects, including data ingest jobs, MLOps workflows, and project architecture. Furthermore, you will identify and track key performance indicators to be shared both internally and with company stakeholders, and initiate the incorporation of emerging technology and open-source projects to drive overall engineering goals.