Senior ML Platform Engineer - Graph ML & MLOps

Aimlroles; Northern (KY); Hybrid; USD 217,000 - 303,000; Full time

Benefits offered by this job

Equity (RSUs)

Commission potential

Health insurance (medical)

Dental insurance

Vision insurance

401(k) with employer match

Paid time off

Parental leave

Job summary

Reddit is seeking a Senior ML Infrastructure Engineer to lead the design and development of a platform for large-scale ML models. You will drive end-to-end ML lifecycle patterns, enabling efficient data prep, model management, and experiment tracking across a distributed environment.

You will optimize training performance, cost, and scalability while collaborating with ML engineers and data teams. The role emphasizes reliability, scalability, and user-focused tooling across cloud-based

Qualifications

• 5+ years of experience in ML infrastructure, including model training and deployment.
• Hands-on experience with ML optimization, including memory and GPU profiling.
• Cloud-based technologies for ML platforms (GCP BigQuery, Google Cloud Storage, Terraform).
• Experience with MLOps tools for experiment tracking, model serving, and registries (MLflow or Wandb).
• Proficiency with Python, PyTorch, TensorFlow.
• Experience with distributed training frameworks (Ray, Kubernetes).
• Strong focus on scalability, reliability, performance, and user-centric design.

Responsibilities

• Design end-to-end ML platform lifecycle patterns to boost development velocity.
• Lead zero-to-one development of a graph ML codebase and platform for scalability.
• Collaborate with ML engineers to optimize training time, cost, and performance.
• Optimize batch data processing using Beam, Spark, Ray Data, and related tools.
• Architect pipelines to manage massive graph data structures at scale.

Skills

ML infrastructure

Python

PyTorch

TensorFlow

Kubernetes

Terraform

GCP BigQuery

Distributed training

GPU profiling

Graph ML

Tools

Apache Beam

Apache Spark

Ray Data

Terraform

MLflow/WandB

Job description

Reddit is seeking a Senior ML Infrastructure Engineer to lead the design and development of a platform for large-scale ML models. You will drive end-to-end ML lifecycle patterns, enabling efficient data prep, model management, and experiment tracking across a distributed environment.

You will optimize training performance, cost, and scalability while collaborating with ML engineers and data teams. The role emphasizes reliability, scalability, and user-focused tooling across cloud-based