Senior ML Infrastructure Engineer | Remote Options

Matchgroup; West Hollywood (CA); On-site; USD 190,000 - 246,000; Full time

Job summary

Matchgroup seeks a senior ML infrastructure engineer to design, build, and maintain scalable ML platforms that support experimentation, training, deployment, and monitoring of models handling massive data sets. The role emphasizes platform engineering, self-service capabilities, and cross-team collaboration.

You will optimize compute/storage, implement A/B testing, and work with Spark, Kafka, Flink, Databricks, and various ML serving tools.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, or related field required.
• 5+ years of professional experience in ML infrastructure or backend software engineering.
• Experience designing large-scale distributed ML platforms using big data tech.

Responsibilities

• Design, build, and maintain scalable ML platform systems and data infra.
• Deploy, monitor, and optimize ML production systems with observability tooling.
• Lead technical initiatives across multiple engineering teams and mentor juniors.
• Contribute to CI/CD pipelines and GitOps practices for ML infra.

Skills

ML infrastructure

Distributed systems

Backend services

Data pipelines

Technical leadership

Education

Bachelor's degree in CS/CE or related field

Master's degree preferred

Tools

Apache Spark

Apache Kafka

Apache Flink

Databricks

Python

Scala

Java

Go

AWS

Azure

GCP

Terraform

Terragrunt

Helm

Docker

Kubernetes (EKS/ECS)

Prometheus

Grafana

Grafana Mimir

Ray Serve

Triton

Delta Lake

Redis

DynamoDB

Snowflake/Redshift/Data warehouse

Job description

Matchgroup seeks a senior ML infrastructure engineer to design, build, and maintain scalable ML platforms that support experimentation, training, deployment, and monitoring of models handling massive data sets. The role emphasizes platform engineering, self-service capabilities, and cross-team collaboration.

You will optimize compute/storage, implement A/B testing, and work with Spark, Kafka, Flink, Databricks, and various ML serving tools.