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Artificial Intelligence • Cloud • Consumer Web • Productivity • Software • App development • Data Privacy
Lead global field and partner marketing to drive Sales-Led Growth (SLG) and partner-sourced pipeline. Own regional GTM strategy, ABM, mid-to-bottom funnel demand, partner co-marketing with AI ecosystems, PLG-to-SLG monetization, sales alignment, events, and scaling a multi-disciplinary global marketing team tied to pipeline outcomes.
Top Skills:
AbmChatgptClaudeCloud MarketplacesCRMGeminiIntent Data PlatformsMapPrm
Artificial Intelligence • Cloud • Consumer Web • Productivity • Software • App development • Data Privacy
Lead design vision and execution for Dropbox's multi-product ecosystem, crafting high-trust AI-powered experiences that activate customer content. Drive strategy through execution, mentor designers, partner with cross-functional teams, and raise design quality across interaction, systems, prototyping, and implementation to deliver elegant, trustworthy product experiences.
Artificial Intelligence • Cloud • Consumer Web • Productivity • Software • App development • Data Privacy
The Staff Product Manager will define and execute the product vision and strategy for Stacks and project context experiences, collaborating cross-functionally, and helping users navigate complex workflows and systems.
Top Skills:
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Role DescriptionResponsibilities
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
Our Engineering Career Framework is viewable by anyone outside the company and describes what’s expected for our engineers at each of our career levels. Check out our blog post on this topic and more here.
- BS, MS, or PhD in Computer Science, Mathematics, Statistics, or a related quantitative field (or equivalent work experience).
- 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, or similar).
- Strong proficiency in Python (required) and experience with systems languages like Go or C/C++. You should be comfortable building the infrastructure that surrounds the model.
- Extensive experience working with large-scale distributed data systems and high-throughput production environments.
- Exceptional analytical skills and a "bias to action" when navigating ambiguous technical challenges.
Many teams at Dropbox run Services with on-call rotations, which entails being available for calls during both core and non-core business hours. If a team has an on-call rotation, all engineers on the team are expected to participate in the rotation as part of their employment. Applicants are encouraged to ask for more details of the rotations to which the applicant is applying.
Requirements- BS, MS, or PhD in Computer Science, Mathematics, Statistics, or a related quantitative field (or equivalent work experience).
- 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, or similar).
- Strong proficiency in Python (required) and experience with systems languages like Go or C/C++. You should be comfortable building the infrastructure that surrounds the model.
- Extensive experience working with large-scale distributed data systems and high-throughput production environments.
- Exceptional analytical skills and a "bias to action" when navigating ambiguous technical challenges.
- PhD with a focus on Deep Learning, NLP, or Reinforcement Learning (RLHF/RLAIF).
- Proven track record of taking AI products from concept to launch, either at a massive scale (millions of users) or by leading multiple 0 → 1 cycles in a fast-paced environment.
- 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 to improve performance and cost-efficiency.
US Zone 1
$245,200—$331,800 USD
US Zone 2
$220,700—$298,700 USD
US Zone 3
$196,200—$265,400 USD
Dropbox Chicago, Illinois, USA Office
Chicago, IL, United States
What you need to know about the Chicago Tech Scene
With vibrant neighborhoods, great food and more affordable housing than either coast, Chicago might be the most liveable major tech hub. It is the birthplace of modern commodities and futures trading, a national hub for logistics and commerce, and home to the American Medical Association and the American Bar Association. This diverse blend of industry influences has helped Chicago emerge as a major player in verticals like fintech, biotechnology, legal tech, e-commerce and logistics technology. It’s also a major hiring center for tech companies on both coasts.
Key Facts About Chicago Tech
- Number of Tech Workers: 245,800; 5.2% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: McDonald’s, John Deere, Boeing, Morningstar
- Key Industries: Artificial intelligence, biotechnology, fintech, software, logistics technology
- Funding Landscape: $2.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Pritzker Group Venture Capital, Arch Venture Partners, MATH Venture Partners, Jump Capital, Hyde Park Venture Partners
- Research Centers and Universities: Northwestern University, University of Chicago, University of Illinois Urbana-Champaign, Illinois Institute of Technology, Argonne National Laboratory, Fermi National Accelerator Laboratory
