Staff Machine Learning Software Engineer, New Initiatives

Key Skills

Aartificial intelligence, Analytical and Problem solving, C Programming, C++, Deep Learning, Effective communication skills, HuggingFace, Large Language Models - LLMs, Machine learning techniques, Python Programming, PyTorch

Job Description

Team Description

Our Engineering team is working to simplify the way people work together. They’re building a family of products that handle over a billion files a day for people around the world. With our broad mission and massive scale, there are countless opportunities to make an impact.

Role Description

As a Staff Machine Leaning Engineer for this new division, you will be able to drive the future direction of a new initiative and push the boundaries on what the world thinks is possible by leveraging the latest advancements in 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.

As a ground floor opportunity for this startup team, we need this staff engineer to build a top-tier truth-seeking culture with a lot of focus on impact and execution!

Responsibilities

• You will serve as the ML thought leader to adopt and get ahead in the fast evolving landscape of ML
• You will design, build, evaluate, deploy and iterate on machine learning models with thousands to billions of parameters (or more!)
• You will push the limits of whats considered possible at scale and generate gains by leveraging the latest development in AI
• You will work across teams and functions to bring your models, and features not considered possible before to life

Requirements

• BS, MS, or PhD in Computer Science, Mathematics, Statistics, or other quantitative fields or related work experience
• 10+ years of engineering experience with 6+ years building Machine Learning or AI systems
• Experience working in a start-up or in a start-up like environment
• Strong industry experience working with large scale data systems
• Strong analytical and problem-solving skills
• Familiarity with the latest development in LLMs
• Proven software engineering skills across multiple languages including but not limited to Python
• Experience with Machine Learning software tools and libraries (e.g. TF, PyTorch, HuggingFace, LangChain etc.)

Preferred Qualifications

• PhD in Computer Science or related field with research in machine learning
• 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
• Experience with one or more of the following: Recommendation Systems, Search, Large Language Models (LLMs)

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:

• Competitive medical, dental and vision coverage*
• Retirement Savings through a defined contribution pension or savings plan**
• Dropbox provides a Flexible PTO Policy in addition to your statutory holidays allowing you to unplug, unwind, and refresh
• Dropbox also provides exclusive additional paid time off for all FTE employees across the Globe, in addition to any relevant statutory holidays
• Protection Plans including Life and Disability Insurance*
• A Perks Allowance to be used on what matters most to you, whether that’s wellness, learning and development, food & groceries, and much more
• Parental benefits including; Parental Leave, Fertility Benefits, Adoptions and Surrogacy support, and Lactation support

Additional benefits details are available upon request.

*Where group plans are not available, allowances are provided

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

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, Latinx, Pridebox (LGBTQ), Vets at Dropbox, Women at Dropbox, ATX Diversity (based in Austin, Texas) and the Dropbox Empowerment Network (based in Dublin, Ireland).