Director, Data Platform Engineering
Lila Sciences is seeking a highly motivated and experienced engineering leader to oversee our product data platform. This role involves full ownership of the data platform and infrastructure, encompassing architecture, delivery, reliability, and enhancing the experience for developers and data scientists. Our mission is to deliver Scientific Super Intelligence through a reliable, scalable, and self-service infrastructure for data ingestion, storage, processing, and interaction, enabling AI/ML, product teams, and scientists to build data-intensive applications with confidence and speed. Our platform supports analytical and machine learning workloads across Lila, serving autonomous DBTL cycles, instrument data pipelines, and AI inference workflows.
Key responsibilities include building, mentoring, and managing a high-performing team of 8-12 data engineering experts. The role requires evaluating and adopting modern data infrastructure, such as real-time streaming technologies (Kafka, Flink), columnar engines (DuckDB, ClickHouse), lake house architectures, and cloud-native object storage solutions. The Director will foster a culture of collaboration, innovation, and continuous improvement, provide technical guidance and mentorship, conduct performance reviews, and manage team workload to ensure timely delivery of high-quality solutions. Additionally, the role involves defining and executing the technical roadmap for our data platform, driving innovation in data Lakehouse and data serving ecosystems, ensuring the reliability, availability, and security of our data processing infrastructure, and collaborating with other engineering teams to integrate our data processing technologies with other Lila systems and services.
The ideal candidate will have over 12 years of software development experience, focusing on data processing at scale, and at least 5 years of experience leading senior engineers. Proficiency in building on AWS/GCP primitives like S3, Athena, and BigQuery, as well as operating data platforms at petabyte scale with sub-second query latency requirements, is essential. Experience managing data infrastructure supporting over 100 concurrent ML training and inference workloads, familiarity with LLM/AI-native data patterns, and a track record of building data platforms in high-growth or early-stage environments are also required. Hands-on coding experience in Python and modern backend frameworks, along with expertise in infrastructure-as-code and containerized deployments (Kubernetes), is necessary. A BS, MS, or Ph.D. in Computer Science or a related field is required.
We offer competitive compensation, including bonus potential and generous early equity. The final offer will reflect your unique background, expertise, and impact. The expected base salary range is $232,000 to $346,000 USD. Full-time U.S. employees receive a comprehensive benefits program, including medical, dental, and vision coverage.
Lila Sciences is the world’s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science. We are pioneering a new age of boundless discovery by building the capabilities to apply AI to every aspect of the scientific method. We are introducing scientific superintelligence to solve humankind's greatest challenges, enabling scientists to bring forth solutions in human health, climate, and sustainability at a pace and scale never experienced before. If this sounds like an environment you’d love to work in, even if you only have some of the experience listed above, we encourage you to apply.