Machine Learning Engineer

• Design, code, train, test, deploy, and iterate on large-scale ML and LLM systems across cloud and mobile/edge environments
• Build delightful, privacy-first product experiences (e.g., intelligent search, document understanding, recommendations, and AI assistants) in partnership with Engineering, Product, and Design
• Lead end-to-end LLM workflows: data curation, prompt engineering, retrieval-augmented generation (RAG) pipelines, tool use/agents, and fine-tuning (e.g., instruction tuning, LoRA/adapters) with rigorous evaluation
• Develop and maintain production-quality services for training and serving, including scalable APIs, vector/feature stores, and streaming/ETL data pipelines
• Optimize for latency, cost, and quality using techniques like quantization, distillation, caching, batching, and autoscaling; tailor models for on-device vs. cluster execution
• Establish robust offline/online evaluation: experiment design, A/B testing, guardrails and safety checks, hallucination mitigation, and automated monitoring/observability with clear SLOs
• Communicate technical trade-offs, risks, and impact to cross-functional stakeholders; write clear design docs, roadmaps, and decision records
• Partner with Security, Legal, and Privacy to ensure responsible AI, data governance, and compliance in training and inference
• Proactively explore and integrate advances in ML/AI (CV, NLP, recsys, LLMs) and rapidly prototype and transfer promising research into production
• Mentor teammates, contribute to code reviews and best practices, and help shape the technical direction of ML and AI at Dropbox
• Participate in on-call rotations for services where applicable

Senior Machine Learning Engineer, Conversational AI

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