Staff Machine Learning Systems Engineer

Stack

Responsibilities

• ▹Design end-to-end MLOps model lifecycle patterns to boost ML engineer velocity
• ▹Zero-to-one development and support of a graph ML codebase and platform
• ▹Collaborate on performance tuning, training time, efficiency and GPU costs
• ▹Optimize batch data processing (Apache Beam, Spark, Ray Data)
• ▹Architect pipelines for graph data structures with billions of nodes and tens of billions of edges

Requirements

• ▹8+ years of ML infrastructure experience, including model training and deployment
• ▹Hands-on ML optimization, including memory and GPU profiling
• ▹Deep experience with cloud technologies (GCP BigQuery, GCS, Terraform)
• ▹Hands-on experience administering MLOps tools (MLflow, Wandb)
• ▹Proficiency in Python, PyTorch, TensorFlow
• ▹Deep experience with distributed training frameworks (Ray, Kubernetes)

Nice to have

• ▹Experience with graph databases (Neo4j, JanusGraph, TigerGraph)
• ▹Experience with graph neural networks and frameworks (PyTorch Geometric, Deep Graph Library)

Soft skills

What we offer

• ▹Medical, dental and vision insurance
• ▹401k program with employer match
• ▹Generous time off and parental leave
• ▹Competitive base salary ($230,000–$322,000) plus equity

About the company

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