Mozilla
Senior Machine Learning Engineer, Applied AI Modeling
Rol remoto de Firefox con fit claro de ubicación del candidato.
PublicadoAgregado recientemente
Países elegibles1 país aceptado
Señal de senioritySenior
Modelo de trabajoRemoto
Ubicaciones aceptadas para candidatos
Estados Unidos
Resumen del rol
Senior Machine Learning Engineer, Applied AI Modeling
Requisitos y responsabilidades
Contenido del rol extraído en secciones para revisar más rápido.
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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