GenAI ML Systems Engineer - Distributed Training & Serving

Meta; New York (NY); On-site; USD 122,000 - 181,000; Full time

Job summary

Meta is expanding its Systems ML Engineering team to design and optimize scalable ML training and inference pipelines. You will contribute to data processing, feature handling, and model serving infrastructure across large-scale distributed environments.

You will work with researchers and product engineers to translate model requirements into robust, high-throughput systems, participating in staged rollouts and ensuring code quality with reviews and documentation.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, or related field, or equivalent practical experience.
• 2+ years of software engineering focusing on ML systems or distributed data infrastructure.
• Experience writing production-quality code in Python and a compiled language (C++/Java).
• Experience designing ML training or inference pipelines (data preprocessing, model execution, serving).
• Experience with distributed computing concepts like data/model parallelism in ML workloads.
• Experience writing automated tests, logging, alerting, and production incident response.

Responsibilities

• Design scalable systems for distributed ML training and inference, including data ingestion pipelines and model serving infrastructure.
• Develop and optimize ML platform components like training orchestration and gradient communication.
• Profile performance and diagnose bottlenecks across the ML stack; optimize latency and throughput.
• Write automated tests and build monitoring/alerting for production anomalies.
• Collaborate with ML researchers and engineers to translate model requirements into reliable system designs.
• Own technical design for ML infrastructure features, balancing throughput, latency, and cost.

Skills

Python

C++

Java

Distributed systems

ML systems

Automated tests

Education

Bachelor's degree in CS/Engineering or equivalent

Tools

PyTorch

JAX

Apache Spark

Flink

Kafka

Job description

Meta is expanding its Systems ML Engineering team to design and optimize scalable ML training and inference pipelines. You will contribute to data processing, feature handling, and model serving infrastructure across large-scale distributed environments.

You will work with researchers and product engineers to translate model requirements into robust, high-throughput systems, participating in staged rollouts and ensuring code quality with reviews and documentation.