Key skills
Machine learningNatural language processingGenerative AILarge language modelsFine-tuning LLMsPrompt engineeringEmbedding-based retrievalEvaluation strategies for generative applicationsML toolingHugging FaceLangChainWeights & BiasesRayModel development lifecycleUser-facing AI featuresOn-device model optimizationPrivacy-preserving MLWeb technologiesOpen-source ML frameworksAIMachine LearningMLNatural Language ProcessingLarge Language ModelsRAGCommunication
About this role
Mozilla Corporation is a non-profit-backed technology company known for shaping the internet positively over the past 25 years. They are seeking a Senior Machine Learning Engineer to develop and fine-tune large language models for intelligent browser interactions, collaborating with various teams to enhance user experiences in Firefox.
Responsibilities:
- 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
Requirements:
- 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
- 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