Senior Machine Learning Engineer, Applied AI Modeling

Role Description

The Firefox team is building the next generation of intelligent, privacy-aware experiences for the web. As part of this evolution, we are embedding modern AI and LLM-driven features directly into the browser—empowering users while safeguarding their autonomy and data.

We’re looking for a Senior Machine Learning Engineer with a strong focus on applied AI and modern LLM-based applications. You will help conceptualize, prototype, and deploy user-facing experiences grounded in Generative AI, working collaboratively with engineering, design, and product to bring these capabilities to life in Firefox.

What You’ll Do

• 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.

Qualifications

• 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.

Requirements

• 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.

Benefits

• 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).