Senior Machine Learning Software Engineer

Remote - Canada

Dropbox

Dropbox helps you simplify your workflow. So you can spend more time in your flow.

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Role Description

At Dropbox, our pursuit of excellence in Machine Learning and Artificial Intelligence fuels our mission to empower users worldwide. We've cultivated a culture rooted in meticulous attention to detail, unwavering commitment to reliability, and a drive to innovate at scale.   As a Senior Machine Leaning Engineer, you will be involved in shaping the future direction of the organization and pushing the boundaries on what the world thinks is possible by leveraging the latest advancements in AI/ML. You will join a team of top-tier Machine Learning Engineers and be an inherent part of the product org to create and build delightful new experiences.    Collaborating closely with cross-functional teams, you'll leverage your ML expertise to tackle audacious challenges. Your contributions will directly impact millions of users, as every line of code you write furthers our mission to revolutionize the way people work and collaborate.

Responsibilities

  • Design, build, evaluate, deploy and iterate on large scale Machine Learning systems
  • Understand the Machine Learning stack at Dropbox, and build systems that help Dropbox personalize their users’ experience
  • Work with Product, Design, Infra and Frontend teams to bring your models, and features to life
  • Work with large scale data systems, and infrastructure
  • Evaluate the performance of machine learning systems against business objectives, and productionize those models
  • Contribute to team’s technical strategy for the end-to-end machine learning lifecycle, ensuring alignment with business objectives and driving impactful outcomes

Requirements

  • BS, MS, or PhD in Computer Science, Mathematics, Statistics, or other quantitative fields or related work experience
  • 8+ years of engineering experience with 5+ years building Machine Learning or AI systems
  • Strong industry experience working with large scale data
  • Strong collaboration, analytical and problem-solving skills
  • 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., Scikit-learn, TensorFlow, Keras, PyTorch, HuggingFace, LangChain 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

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.

Total Rewards

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.

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). 

Current Salary/OTE Ranges (Subject to change):
C$193,000 - C$227,000 - C$261,000

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: Bayesian Computer Science Deep Learning Engineering HuggingFace Keras LangChain LLMs Machine Learning Mathematics NLP PhD Python PyTorch Recommender systems Research Scikit-learn Statistics TensorFlow

Regions: Remote/Anywhere North America
Country: Canada
Job stats:  31  5  0

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