Molecular AI ML Infrastructure Engineer — Fast Pipelines

Genesis Molecular AI; San Mateo (CA); On-site; USD 140,000 - 210,000; Full time

Benefits offered by this job

Health benefits

401(k) plan

Open PTO

Free lunches and dinners

Family leave

Disability insurance

Job summary

Genesis Molecular AI seeks a Machine Learning Infrastructure Engineer to build data and orchestration systems powering molecular AI. You will design and optimize our in-house orchestration framework and the data preprocessing pipelines that run on top of it.

You will collaborate with ML researchers, computational chemists, and software engineers to reduce latency, enable lazy evaluation and caching, and improve reproducibility across complex scientific workflows.

Qualifications

• Experience building or operating large-scale ETL, data processing, or workflow systems.
• Familiarity with Kubernetes and containerized compute environments.
• Experience with cloud object storage and high-performance computing.
• Knowledge of molecular data formats and tools a plus.

Responsibilities

• Design and evolve our in-house workflow orchestration framework: DAG construction, execution, scheduling, caching, observability.
• Build and optimize large-scale preprocessing pipelines for protein structures and chemical datasets.
• Profile workflows to remove bottlenecks and reduce latency across distributed systems.
• Develop abstractions for lazy execution and artifact reuse to avoid unnecessary recomputation.
• Collaborate with ML researchers and scientific software engineers to translate workflows into scalable pipelines.
• Improve developer experience for researchers and engineers working on pipelines.

Skills

DAGs

Distributed systems

Data-intensive pipelines

Workflow orchestration

Performance optimization

Caching & memoization

Python & engineering

Cloud & Kubernetes

ETL pipelines

Education

Experience with data-intensive systems or equivalent

Tools

Apache Spark

GCP Dataflow / Apache Beam

Dagster

Airflow

Kubernetes

Terraform

Open source workflow engines

Job description

Genesis Molecular AI seeks a Machine Learning Infrastructure Engineer to build data and orchestration systems powering molecular AI. You will design and optimize our in-house orchestration framework and the data preprocessing pipelines that run on top of it.

You will collaborate with ML researchers, computational chemists, and software engineers to reduce latency, enable lazy evaluation and caching, and improve reproducibility across complex scientific workflows.