
Senior Machine Learning Engineer, Conversational AI
- Canada
- Permanent
- Temps-plein
- 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
- BS or MS in Computer Science or related technical field involving Machine Learning or equivalent technical experience
- 8+ years of experience in engineering with 5+ years of experience building Machine Learning or AI systems
- Strong industry experience working with large scale data
- Strong analytical and problem-solving skills
- Familiarity with search-related applications of Large Language Models
- Proven software engineering skills across multiple languages including but not limited to Python, Go, C/C++
- Experience with Machine Learning software tools and libraries (e.g., PyTorch, HuggingFace, TensorFlow, Keras, Scikit-learn, etc.)
- PhD in Computer Science or related field with research in machine learning
- Experience with one or more of the following: natural language processing, deep learning, bayesian reasoning, recommender systems, learning to rank, speech processing, learning from semistructured data, graph learning, reinforcement or active learning, large language models, ML software systems, retrieval-augmented generation, machine learning on edge devices
- Experience building 0→1 ML products at large (dropbox-level) scale or multiple 0→1 products at smaller scale including experience with large-scale product systems
- Flexible PTO/Paid Time Off, paid holidays, Volunteer Time Off, and more, allowing you time to unplug, unwind, and refresh
- Perks Allowance to be used on what matters most to you, whether that's wellness, learning and development, food and groceries, and much more
- Mental health and wellness benefits
- Monthly Internet Allowance
- Intern Social Stipend
- Annual Emerging Talent Summit, travel and hotel accommodations provided