Remote ML Performance Engineer: Inference & Systems

Fdetimes; United States; Remote; USD 217,000 - 303,000; Full time

Benefits offered by this job

Global Benefit programs that fit your、

Family Planning Support

Gender-Affirming Care

Mental Health & Coaching Benefits

Group Personal Pension Scheme with EMI

Private Medical and Dental Scheme

Income Replacement Programs

Bike to Work scheme

Flexible Vacation & Paid Volunteer 时间

Generous Paid Parental Leave

Job summary

Reddit is hiring for an ML Performance Engineer to optimize production ML workloads across inference, training, and serving paths. You will profile bottlenecks, implement runtime and kernel level improvements, and drive end-to-end performance gains with safe rollout practices.

You will collaborate with ranking, serving, and platform teams, build reusable benchmarks, and mentor engineers while maintaining model quality and reliability.

Qualifications

• Hands-on ML performance engineering experience in production or production-relevant workloads.

Responsibilities

• Own end-to-end performance optimization initiatives for high-impact production ML workloads.
• Profile and diagnose ML performance bottlenecks across model execution, frameworks, runtimes, memory, CPU/GPU utilization, and infrastructure.
• Design and implement performance improvements involving inference execution, runtime behavior, batching, memory management, precision, compiler integration, custom operators, kernels, or other relevant techniques.
• Improve ML training and serving efficiency and scalability, optimizing latency, throughput, hardware utilization, and cost while maintaining model quality and production reliability.
• Support faster and safer model launches through performance benchmarking, load testing, regression detection, and launch-readiness improvements.
• Partner with model engineers and platform teams to identify high-leverage opportunities, integrate optimizations safely, and validate measurable end-to-end impact.
• Build reusable performance capabilities, including benchmarks, tooling, optimization patterns, and engineering guidance that accelerate future model development and deployment.
• Contribute to technical direction and mentor engineers through hands-on collaboration, code reviews, performance debugging, and knowledge sharing.

Skills

ML performance engineering

Profiling & benchmarking

Python

Systems programming

ML systems understanding

Production engineering judgment

Communication

Problem solving

Tools

PyTorch

TensorRT

ONNX Runtime

CUDA

Triton

LLVM/MLIR

Job description

Reddit is hiring for an ML Performance Engineer to optimize production ML workloads across inference, training, and serving paths. You will profile bottlenecks, implement runtime and kernel level improvements, and drive end-to-end performance gains with safe rollout practices.

You will collaborate with ranking, serving, and platform teams, build reusable benchmarks, and mentor engineers while maintaining model quality and reliability.