Resumo da vaga

Senior Machine Learning Engineer, Applied AI Modeling

Requisitos e responsabilidades

Conteúdo da vaga extraído em seções para revisão mais rápida.

Details

  • Develop and fine-tune large language models (LLMs) for intelligent, safe, and responsive browser interactions.
  • Apply retrieval-augmented generation (RAG), summarization, classification, and intent modeling techniques in real-world browser workflows.
  • Use modern ML tooling (e.g., Hugging Face, LangChain, Weights & Biases, Ray, or similar) to support end-to-end model development, including experimentation, evaluation, and rollout.
  • Collaborate closely with product and engineering partners to design, iterate, and launch features that align with user needs and Mozilla’s values.
  • Design and implement experiments to test model behavior in production, analyze results, and iterate based on findings.
  • Document and share your work, participating in code reviews and team design discussions.
  • 4+ years of experience in applied machine learning, with a focus on natural language processing or generative AI.
  • Hands-on experience fine-tuning and evaluating LLMs using modern tools and open-source libraries.
  • Strong understanding of prompt engineering, embedding-based retrieval, and evaluation strategies for generative applications.
  • Experience using ML tooling to lead the end-to-end lifecycle of model development—from data exploration to deployment-ready artifacts.
  • Track record of building user-facing AI features, especially where privacy, latency, and usability are critical.
  • Clear communication skills and ability to collaborate with multi-functional partners on a distributed team.
  • Commitment to our values:
  • Welcoming differences
  • Being relationship-minded
  • Practicing responsible participation
  • Having grit
  • Welcoming differences
  • Being relationship-minded
  • Practicing responsible participation
  • Having grit
  • Familiarity with on-device model optimization or privacy-preserving ML.
  • Experience working in a browser context or with web technologies.
  • Contributions to open-source ML frameworks or model hubs.
  • Generous performance-based bonus plans to all eligible employees - we share in our success as one team
  • Rich medical, dental, and vision coverage
  • Generous retirement contributions with 100% immediate vesting (regardless of whether you contribute)
  • Quarterly all-company wellness days where everyone takes a pause together
  • Country specific holidays plus a day off for your birthday
  • One-time home office stipend
  • Annual professional development budget
  • Quarterly well-being stipend
  • Considerable paid parental leave
  • Employee referral bonus program
  • Other benefits (life/AD&D, disability, EAP, etc. - varies by country)
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