Senior Machine Learning Engineer, Dash Agentic AI

Role Description

As a Senior Machine Learning Engineer, you will play a key role in advancing Dropbox's mission to create a more enlightened way of working. Leveraging cutting-edge AI/ML technologies, you will design, build, deploy, and refine highly reliable AI agents operating at massive scale. Your work will power Dropbox Dash's universal agentic search and autonomous organization features, transforming how millions of users collaborate, stay organized, and focus on the work that truly matters.

Responsibilities

• Design and productionize agentic AI frameworks — including multi-agent coordination, planning, tool-use, and memory.
• Lead the end-to-end design of ML systems, from fine-tuning (SFT, RLAIF) and advanced prompting to inference optimization and production monitoring.
• Establish rigorous safety, alignment, and evaluation frameworks to ensure our autonomous systems are helpful, honest, and harmless.
• Collaborate across Product, Design, Infra, and Frontend teams to translate ambiguous user needs into concrete AI capabilities.
• Mentor junior engineers and serve as a core contributor to the broader Dropbox AI strategy.

Requirements

• BS, MS, or PhD in Computer Science, Mathematics, Statistics, or a related quantitative field.
• 8+ years of software engineering experience, with at least 5+ years dedicated to building and deploying production-scale AI/ML systems.
• Professional experience in ML modeling for complex systems such as Search, Ranking, or Recommender Systems.
• Deep familiarity with LLM architectures and hands-on experience with ML libraries (e.g., PyTorch, JAX).
• Strong proficiency in Python (required) and experience with systems languages like Go or C/C++.
• Extensive experience working with large-scale distributed data systems and high-throughput production environments.

Preferred Qualifications

• PhD with a focus on Deep Learning, NLP, or Reinforcement Learning (RLHF/RLAIF).
• Proven track record of taking AI products from concept to launch at massive scale (millions of users).
• Hands-on experience with autonomous agent frameworks, multi-step planning, tool-use (function calling), and advanced RAG.
• Experience with inference optimization, model distillation, or fine-tuning techniques.

Compensation

US Zone 1: $245,200 — $331,800 USD
US Zone 2: $220,700 — $298,700 USD
US Zone 3: $196,200 — $265,400 USD