Staff Machine Learning Engineer, Ads ML Efficiency
Remote - United States · Staff+ · Contract
Sponsorship not specified$230k-$322kDetected 5 days ago
PythonJavaRustC++Distributed SystemsCloud PlatformsMachine LearningTensorFlowPyTorchSparkData EngineeringLLMsA/B TestingMentoring
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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.
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About the role
- We focus on improving developer productivity, reducing infrastructure costs, increasing hardware utilization, and accelerating experimentation across the company's ML ecosystem.
Responsibilities
- Design and build systems that improve the efficiency of ML training and inference workloads.
- Develop tooling that helps ML engineers debug, profile, optimize, and monitor model performance.
- Partner with ML researchers and product teams to identify bottlenecks and drive performance improvements.
- Build benchmarking frameworks and performance dashboards for training and serving systems.
- Optimize distributed training infrastructure, data pipelines, and model serving architectures.
- Lead cross-functional initiatives that improve the productivity of Reddit ML engineers.
- Drive technical strategy for ML platform scalability, reliability, and cost efficiency.
- Teams spend less time managing infrastructure and more time building models.
- Family Planning Support
Requirements
- 5+ years of software engineering experience.
- Strong proficiency in Python
- Experience with large-scale recommendation, ranking, generative AI, or foundation model systems.
- Experience with distributed training frameworks such as PyTorch Distributed, Ray, Tensorflow, Spark
- Familiarity with GPU architectures and performance analysis tools.
- Experience optimizing cloud infrastructure costs across large ML workloads.
- Experience with building real time ML inference applications
- Required
- BS, MS, or PhD in Computer Science or a related field.
- Experience building distributed systems at scale.
- Experience with machine learning infrastructure, training systems, or model serving platforms.
- Deep understanding of performance engineering and systems optimization.
- Strong debugging and profiling skills.
- Preferred
Nice to have
- Profiency in at least one systems language (Go, C++, Rust, or Java) preferred
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
- The ML Efficiency team builds the infrastructure, tooling, and optimization systems that enable machine learning engineers and researchers to train, evaluate, deploy, and operate models efficiently at scale.
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.