Job Description

Dropbox is a Virtual First company. For this role, we are currently only authorized to hire candidates from the following provinces: Alberta, British Columbia, Ontario, and Saskatchewan.



Role Description



Machine Learning Engineers at Dropbox develop high-impact products that advance Dropbox's mission of designing a more enlightened way of working. Dropbox MLE's deliver products using the full range of ML techniques--including computer vision, natural language processing, recommendation systems, large language models (LLMs), and LLM-driven agents--and modern practices such as LLM fine-tuning, prompt engineering, and retrieval-augmented generation (RAG).While some of our algorithms run on mobile devices, others require large clusters on our infrastructure. Accordingly, we apply techniques like model compression, distillation, on-device optimization, and scalable training/serving with robust evaluation and monitoring.



Dropbox is looking for Machine Learning Engineers with an academic or practical background in ML, ideally with experience in natural language understanding, information retrieval, knowledge extraction, or deep learning, as well as hands-on work with LLMs (pre-training and fine-tuning, including instruction tuning and LoRA/adapters), prompt engineering, RAG pipelines, safety/guardrails and evaluation, and productionizing generative and predictive systems.



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 .



Responsibilities



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



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 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.)

Preferred Qualifications



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



Compensation



Canada Pay Range $199,800--$270,300 CAD



The range listed above is the expected annual salary/OTE for this role, subject to change.



Salary/OTE is just one component of Dropbox's total rewards package. All regular employees are also eligible for the corporate bonus program or a sales incentive (target included in OTE) as well as stock in the form of Restricted Stock Units (RSUs).



Company Description



Dropbox isn't just a workplace--it's a living lab for more enlightened ways of working. We're a global community of bold visionaries and resourceful doers who are shaping the future of Dropbox--and with it the future of work. Our Virtual First model combines the autonomy of a distributed workplace with the power of human connection, making space for both meaningful work and meaningful relationships. With our start-up mindset and enterprise-level opportunities, you can be who you are and grow into who you're meant to be. Here, you can own your impact to make work more intuitive, joyful, and human--for you as a Dropboxer and for hundreds of millions of people worldwide. If you're ready to push boundaries--and yourself-- Dropbox is ready for you.



Team Description



The Dropbox Engineering Team builds the technology that creates more enlightened ways of working for hundreds of millions of people. Every day, our platforms--including Dropbox Dash, Dropbox Sign, and our core sync engine--handle over a billion files for users worldwide, creating engineering challenges as great as the opportunity for impact. Our software engineering team uses a range of technologies to solve interesting problems, including Python, React, Node.js, JavaScript, MongoDB, PostgreSQL, and Android development. We think like a startup but build for an enterprise, exploring new possibilities that transform how people work. If you're excited about turning complex technical challenges into intuitive solutions at scale, join our Engineering team.



Areas of work include Machine Learning Engineers, Infrastructure Engineer, Product SWE Frontend and Backend, Mobile Software Engineers (iOS and Android), Engineering Manager, Data Engineer, Software Development Engineer in Test, Security Engineering, Site Reliability Engineer, Technical Program Managers, Network Engineer, Datacenter Engineer, Technical Supply Chain Manager and more.



Benefits



Dropbox is committed to investing in the holistic health and wellbeing of all Dropboxers and their families. Our benefits and perks programs include, but are not limited to:



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



Additional benefits details are available upon request.



Where group plans are not available, allowances may be provided

Benefit, amount, and type are dependent on geographical location, based upon applicable law or company policy



Dropbox supports responsible use of AI for preparation, but misrepresentation of skills or experience is not permitted. See our AI philosophy .



Dropbox is an equal opportunity employer. We are a welcoming place for everyone, and we do our best to make sure all people feel supported and connected at work. A big part of that effort is our support for members and allies of internal groups like Asians at Dropbox, BlackDropboxers, enABLE, TODOS (Latinx), Pridebox (LGBTQ), Vets at Dropbox, and Women at Dropbox.