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Staff Software Engineer, Communication Products

Full-stack EngineerSoftware EngineerFull TimeRemoteTeam 5,001-10,000Since 2007H1B SponsorCompany SiteLinkedIn

Location

United States

Posted

14 days ago

Salary

$204K - $255K / year

Bachelor Degree9 yrs expEnglish

Job Description

• Design, build, and operate the systems that serve ML models within the messaging stack, with a focus on latency, reliability, and scalability • Write and review technical designs that solve large, open-ended problems at the intersection of ML and product engineering without clearly-known solutions • Partner with ML, data science, and product teams to identify high-value opportunities, establish evaluation criteria, and close the gap between offline model performance and production impact • Collaborate with other engineers and cross-functional partners across Messaging, Trust & Safety, Localization, and Platform organizations to align on long-term technical solutions • Mentor, guide, advocate, and support the career growth of individual contributors • Establish engineering standards for ML integration across the messaging surface, including feature flagging, A/B testing, observability, and graceful degradation

Job Requirements

  • 9+ years of relevant engineering hands-on work experience
  • Bachelors, Masters, or PhD in CS or related field
  • Demonstrated experience building and shipping ML-powered product features in production environments, including model serving, feature pipelines, online/offline evaluation, and monitoring
  • Exceptional architecture abilities and experience with architectural patterns of large, high-scale applications
  • Familiarity with NLP/NLU techniques and large language models, particularly as applied to messaging, conversational AI, or content understanding
  • Shipped several large-scale projects with multiple dependencies across teams, specifically at the intersection of ML infrastructure and product engineering
  • Technical leadership and strong communication skills with the ability to translate between ML research, product goals, and engineering execution
  • Experience operating distributed, real-time systems at scale with high reliability requirements
  • Experience with real-time messaging systems or event-driven architectures
  • Familiarity with ML infrastructure at scale (e.g., feature stores, model registries, online inference platforms)
  • Prior work on trust & safety, content moderation, or internationalization in a messaging context
  • Experience with LLM-based product features, including prompt engineering, retrieval-augmented generation, or fine-tuning.

Benefits

  • This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.

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