Senior Machine Learning Engineer

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Senior Machine Learning Engineer in USA

Reddit
Full time
Email

USA
10/21/2026
Report

Remote

Responsibilities

Own production ML performance optimization initiatives from bottleneck identification through implementation, validation, and rollout.
Profile and diagnose bottlenecks across model execution, frameworks, runtimes, memory, CPU/GPU utilization, and infrastructure.
Implement improvements involving inference execution, runtime behavior, batching, memory management, precision, compiler integration, custom operators, and kernels.
Optimize ML training and serving for latency, throughput, hardware utilization, cost, model quality, and reliability.
Support model launches through benchmarking, load testing, regression detection, and launch-readiness improvements.
Partner with model engineering, serving, ranking, and ML Platform teams to integrate and validate optimizations.
Build reusable performance benchmarks, tooling, optimization patterns, and engineering guidance.
Contribute to technical direction and mentor engineers through collaboration, code reviews, debugging, and knowledge sharing.

Requirements

Demonstrated hands-on experience diagnosing and implementing meaningful performance improvements in production or production-relevant ML workloads.
Deep expertise in at least one area such as inference execution, ML runtimes, compiler integration, GPU/kernel optimization, memory systems, or training execution.
Strong profiling and benchmarking skills, including establishing baselines and validating measurable end-to-end improvements.
Strong software engineering fundamentals, including implementing, debugging, testing, and maintaining performance-sensitive systems with proficiency in Python and relevant systems programming technologies.
Understanding of production ML frameworks and trade-offs across model execution, runtime, memory, hardware, and infrastructure.
Ability to balance performance with numerical correctness, model quality, reliability, maintainability, and safe rollout.
Clear communication and ability to explain technical trade-offs to engineers and partner teams.
Experience optimizing large-scale inference or training workloads in recommendation systems, ranking, search, or retrieval is preferred.
Experience with PyTorch performance optimization, distributed-training performance, inference runtimes, GPU execution, hardware-aware optimization, benchmarks, profiling tools, regression detection, or ML cost observability is preferred.
Specialized compiler internals or custom CUDA/Triton kernel development are valuable but not required.

Benefits

Remote work is available from anywhere in the United States or Canada under Reddit’s flexible first workforce model.
Global benefits include workspace support, professional development, and caregiving support.
Family planning support, gender-affirming care, mental health and coaching benefits, medical and dental coverage, income replacement programs, and paid parental leave are offered.
Additional benefits include a group personal pension scheme with employer match, bike-to-work scheme, flexible vacation, and paid volunteer time off.
U.S.-based employees may receive medical, dental, and vision insurance, a 401(k) program with employer match, and generous vacation and parental leave.
The role may include equity in the form of restricted stock units and, depending on the position offered, commission.

Salary: $217k - $303k/yr

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