ML Infrastructure Engineer for Molecular AI Pipelines

Genesis Therapeutics; San Mateo (CA); On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

Salary + equity

Health benefits including Medical, 401

Open PTO

Free meals

Job summary

Genesis Molecular AI in San Mateo, CA seeks a Machine Learning Infrastructure Engineer to design and optimize its in-house orchestration framework and the protein/chemical data pipelines that power molecular AI efforts.

You will split time shaping the DAG-based platform and building scalable data preprocessing pipelines for structural biology and ML data. Collaboration with ML researchers and chemists is essential for reproducible, high-performance workflows.

Qualifications

• Experience building or operating large-scale ETL, data processing, or workflow systems.
• Experience with Kubernetes and containerized compute environments.
• Familiarity with molecular data formats and cheminformatics tools.

Responsibilities

• Design and evolve our in-house workflow orchestration framework, including DAG construction and execution, dependency management, scheduling, caching, retries, observability, and distributed execution.
• Build and optimize large-scale preprocessing pipelines for protein structures, chemical datasets, simulations, and ML training data.
• Profile end-to-end workflows and eliminate bottlenecks—from I/O and serialization to recomputation and parallelization.
• Develop abstractions for lazy execution, incremental computation, caching, and artifact reuse.
• Partner with ML researchers and scientists to translate complex workflows into scalable pipelines.
• Improve developer experience for scientists and engineers authoring pipelines.
• Make architectural decisions spanning local and distributed execution, storage, and data lineage.
• Leverage real-world pipelines to improve the orchestration platform for faster scientific workflows.

Skills

DAGs

Latency optimization

Caching

Distributed systems

Collaborating with researchers

Tools

Apache Spark

Airflow

Dagster

Kubernetes

Terraform

Job description

Genesis Molecular AI in San Mateo, CA seeks a Machine Learning Infrastructure Engineer to design and optimize its in-house orchestration framework and the protein/chemical data pipelines that power molecular AI efforts.

You will split time shaping the DAG-based platform and building scalable data preprocessing pipelines for structural biology and ML data. Collaboration with ML researchers and chemists is essential for reproducible, high-performance workflows.