Senior ML Platform Engineer – Remote | Equity Eligible

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

Benefits offered by this job

Healthcare benefits

401k match

Global benefits programmes

Family planning

Gender-affirming care

Mental health benefits

Flexible vacation & volunteer time off

Parental leave

Job summary

Reddit is seeking a Senior Software Engineer, ML Platform, to architect and maintain foundational ML infrastructure powering Feeds Ranking, Content Understanding, and Recommendations. You will build governance tools and collaborate with MLEs to enable signal ownership, quality, and usage analysis across petabyte-scale pipelines.

You will drive end-to-end projects from planning through rollout, partnering with cross-functional teams to deliver reliable, scalable systems and robust data pipelines

Qualifications

• 5+ years of experience in the ML Platform domain.
• Strong customer focus and cross-functional project delivery experience.
• Experience with large-scale batch and streaming data processing.
• Production-quality systems with testing, monitoring, observability, and reliability practices.
• Deep understanding of distributed systems and data-intensive architectures with strong communication.

Responsibilities

• Lead design, development, testing, and operation of ML signal-governance capabilities.
• Build tools to assess signal importance and lifecycle decisions.
• Partner with MLEs and cross-functional teams to define governance workflows and signal metadata exploration.
• Contribute to ML Data Platform including prediction logging and training data platforms.
• Drive end-to-end delivery of complex projects from planning to rollout and operation.

Skills

ML Platform experience

Distributed systems

Data processing

Job description

Reddit is seeking a Senior Software Engineer, ML Platform, to architect and maintain foundational ML infrastructure powering Feeds Ranking, Content Understanding, and Recommendations. You will build governance tools and collaborate with MLEs to enable signal ownership, quality, and usage analysis across petabyte-scale pipelines.

You will drive end-to-end projects from planning through rollout, partnering with cross-functional teams to deliver reliable, scalable systems and robust data pipelines