Senior ML Engineer - Remote, Ads Ranking & RL

EngineersOfAI

San Francisco (CA)

On-site

USD 180,000 - 280,000

Full time

14 days+
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Benefits offered by this job

Comprehensive Healthcare Benefits and
401k with Employer Match
Global Benefit programs
Family Planning Support
Gender-Affirming Care
Mental Health & Coaching Benefits
Flexible Vacation & Paid VolunteerTime
Generous Paid Parental Leave

Job summary

Reddit is seeking a Senior ML Engineer to design, train, and deploy cutting-edge models powering advertising ranking and optimization. You will lead feature representations, embeddings, and large-scale experiments, collaborating with product and data teams to deliver scalable, reliable systems.

The role emphasizes end-to-end model lifecycle ownership, production readiness, and mentorship across the ML team, with full-time telecommuting as an option.

Qualifications

  • Master’s degree in Computer Science, Engineering (any field) or related quantitative discipline.
  • 3 years of experience in the job offered or related occupation.

Responsibilities

  • Design, train, and deploy advanced ML models for large-scale online advertising.
  • Lead feature representations, embeddings, and cross-session user behavior modeling.
  • Oversee end-to-end model lifecycle, experimentation, deployment, and monitoring.
  • Collaborate with product, data, and infra teams to implement scalable modeling solutions.
  • Provide technical leadership and mentorship to ML engineers.

Skills

Python
Java
Scala
C++
Go
Rust
ML frameworks
Statistics
Experiment design
Data processing
Containerized systems

Education

Master's degree in Computer Science/Engineering

Tools

TensorFlow
PyTorch

Job description

Reddit is seeking a Senior ML Engineer to design, train, and deploy cutting-edge models powering advertising ranking and optimization. You will lead feature representations, embeddings, and large-scale experiments, collaborating with product and data teams to deliver scalable, reliable systems.

The role emphasizes end-to-end model lifecycle ownership, production readiness, and mentorship across the ML team, with full-time telecommuting as an option.

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