Similar Jobs at Dropbox
Artificial Intelligence • Cloud • Consumer Web • Productivity • Software • App development • Data Privacy
Develop and lead integrated B2B marketing campaigns for enterprise product launches and evergreen motions. Define audiences, narratives, buyer journeys, channel roles, activation plans, measurement, and optimization strategies. Orchestrate owned, earned, and paid programs across cross-functional teams, guide campaigns from briefing through post-launch learning, and improve performance through analytics and portfolio insights.
Top Skills:
AIAttribution PlatformsCRMExperimentation PlatformsIntent PlatformsMarketing Automation PlatformsMedia Platforms
Artificial Intelligence • Cloud • Consumer Web • Productivity • Software • App development • Data Privacy
Leads Dropbox’s lifecycle marketing strategy across onboarding, engagement, retention, monetization, expansion, cross-sell, and re-engagement. Manages a team, sets the roadmap, develops scalable customer programs, and partners with Product, Data Science, Marketing Operations, and other teams. Oversees segmentation, personalization, experimentation, measurement, marketing automation, and operating-model development to improve adoption, retention, and revenue.
Top Skills:
Campaign Orchestration ToolsCRMCustomer Data SystemsIterableMarketing Automation Platforms
Artificial Intelligence • Cloud • Consumer Web • Productivity • Software • App development • Data Privacy
Owns a strategic Virtual First technology workstream focused on AI enablement, knowledge management, tool optimization, automation, and modern ways of working. Leads organizational research, pilots, experiments, and a portfolio of cross-functional programs from scoping through adoption. Translates quantitative and qualitative findings into recommendations, operating models, and measurable improvements in employee effectiveness, tool confidence, and technology adoption.
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 Boston, Massachusetts, USA Office
Boston, MA, United States
What you need to know about the Boston Tech Scene
Boston is a powerhouse for technology innovation thanks to world-class research universities like MIT and Harvard and a robust pipeline of venture capital investment. Host to the first telephone call and one of the first general-purpose computers ever put into use, Boston is now a hub for biotechnology, robotics and artificial intelligence — though it’s also home to several B2B software giants. So it’s no surprise that the city consistently ranks among the greatest startup ecosystems in the world.
Key Facts About Boston Tech
- Number of Tech Workers: 269,000; 9.4% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Thermo Fisher Scientific, Toast, Klaviyo, HubSpot, DraftKings
- Key Industries: Artificial intelligence, biotechnology, robotics, software, aerospace
- Funding Landscape: $15.7 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Summit Partners, Volition Capital, Bain Capital Ventures, MassVentures, Highland Capital Partners
- Research Centers and Universities: MIT, Harvard University, Boston College, Tufts University, Boston University, Northeastern University, Smithsonian Astrophysical Observatory, National Bureau of Economic Research, Broad Institute, Lowell Center for Space Science & Technology, National Emerging Infectious Diseases Laboratories
