Senior Machine Learning Engineer, Ads ML Efficiency
Remote - United States · Senior · Contract
Sponsorship not specified$217k-$303kDetected 15 hours ago
PythonCode ReviewMachine LearningPyTorchMLOpsLoad TestingCommunicationCollaborationMentoring
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odds of building a lasting career here
61Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role90
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70
Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.
Lottery odds assume a STEM candidate.
Personalize to your clock →Employer immigration record
from this employer's Department of Labor filings
Green-card filing pattern in this occupation
Context, not a finding about this posting: of this employer's 8 green-card filings in this occupation, 88% were for a worker who already held the job.
Files H-1B transfers
35 transfer filings in the last year, covering 35 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.
Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.
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About the role
- This role sits at the intersection of ML workloads, execution systems, and engineering leverage.
Responsibilities
- Own end-to-end performance optimization initiatives for high-impact production ML workloads, from bottleneck identification and implementation through validation and production rollout.
- Design and implement performance improvements involving inference execution, runtime behavior, batching, memory management, precision, compiler integration, custom operators, kernels, or other relevant techniques.
- 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.
- Hands-on ML performance engineering experience: Demonstrated ability to diagnose and implement meaningful performance improvements in production or production-relevant ML workloads.
- Strong profiling and benchmarking skills: Ability to identify bottlenecks systematically, establish reliable baselines, and validate measurable end-to-end improvements.
- Family Planning Support
Requirements
- Deep expertise in at least one ML performance area, such as inference execution, ML runtimes, compiler integration, GPU/kernel optimization, memory systems, or training execution.
- Strong software engineering fundamentals: Experience implementing, debugging, testing, and maintaining performance-sensitive systems, with proficiency in Python and relevant systems programming technologies.
- Production engineering judgment: Ability to balance performance improvements with numerical correctness, model quality, reliability, maintainability, and safe rollout.
Nice to have
- Experience with PyTorch, including performance optimization using technologies such as Dynamo, Inductor, AOTI, torch.export, or custom operators.
- Experience with inference runtimes, GPU execution, or performance technologies such as TensorRT, ONNX Runtime, CUDA, Triton, LLVM/MLIR, or equivalent systems.
- Experience with hardware-aware optimization, including batching, memory management, operator fusion, mixed precision, quantization, or accelerator efficiency.
- Experience with distributed-training performance, including GPU utilization, communication, data loading, memory efficiency, or training step-time optimization.
- Specialized compiler internals or custom CUDA/Triton kernel development are valuable but not required.
- We value demonstrated performance engineering depth, sound technical judgment, and measurable workload impact over familiarity with any particular tool or framework.
Skills
- Experience optimizing large-scale inference or training workloads, particularly in recommendation systems, ranking, search, or retrieval.
- Experience working across ML modeling, serving, and platform infrastructure teams.
- Good customer and platform instincts: can solve concrete bottlenecks while keeping maintainability, adoption, and future reuse in mind.
- Nice-to-have
Compensation
- In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission.
- To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state.
- We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies.
Benefits
- Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
- Mental Health & Coaching Benefits
- Group Personal Pension Scheme with Employer match
- Private Medical and Dental Scheme
- Flexible Vacation & Paid Volunteer Time Off
- Generous Paid Parental Leave
Company info
- Reddit's Ads ML Efficiency team is focused on making machine learning workloads faster, more scalable, and more cost-efficient, enabling our Ads ML teams to develop, launch, and scale increasingly sophisticated models.
- The engineer will partner closely with ranking teams, serving owners, and ML Platform to identify important bottlenecks, implement targeted improvements, and connect execution and systems improvements to measurable end-to-end outcomes.
- What we're looking for
Equal opportunity
- Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.
- If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.
Visa & Work Authorization
- You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.
This listing is sourced directly from Reddit's careers page and normalized into a canonical job model.