[Remote] Senior Machine Learning Systems Engineer

Note: The job is a remote job and is open to candidates in USA. Reddit is a community of communities, home to the most open and authentic conversations on the internet. The Senior Machine Learning Systems Engineer will lead the development of a platform for large scale ML models, focusing on enhancing model lifecycle patterns and collaborating with ML engineers to optimize performance in a distributed training environment.

Responsibilities

• Design end-to-end model lifecycle patterns (MLOps) to boost velocity of development for ML engineers, including data preparation, model management, experiment tracking, and more
• Zero-to-one development and support of a graph ML codebase and platform that abstracts away common patterns and enables greater model scalability and iteration
• Collaborate with ML engineers on performance tuning, including improving model training time, efficiency, and GPU training costs in a large, distributed ML training environment
• Optimize batch data processing within a data warehouse and with tools such as Apache Beam, Apache Spark, Ray Data, and more
• Architect pipelines to build and maintain massive graph data structures on the order of billions of nodes and tens of billions of edges

Skills

• 5+ years of experience in ML infrastructure, including model training and model deployments
• Hands-on experience with ML optimization, including memory and GPU profiling
• Deep experience with cloud-based technologies for supporting an ML platform, including tools like GCP BigQuery, Google Cloud Storage, infrastructure-as-code (Terraform), and more
• Hands-on experience administering and integrating MLOps tools for experiment tracking, model serving, and model registries (e.g. MLflow or Wandb)
• Proficiency with the common programming languages and frameworks of ML, such as Python, PyTorch, Tensorflow, etc
• Deep experience working with distributed training frameworks, including Ray and Kubernetes
• Strong focus on scalability, reliability, performance, and ease of use. You are an undying advocate for platform users and have a deep intuition for the machine learning development lifecycle
• Strong organizational & communication skills
• Experience working with graph databases (Neo4j, JanusGraph, TigerGraph) is a big plus
• Experience working with graph neural networks (GNNs) and associated graph ML frameworks (PyTorch Geometric, Deep Graph Library) is a big plus

Benefits

• Equity in the form of restricted stock units
• Depending on the position offered, it may also be eligible to receive a commission
• Medical, dental, and vision insurance
• 401(k) program with employer match
• Generous time off for vacation
• Parental leave
• Opt out of recording, transcription and summarization prior to any scheduled interviews

Company Overview

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