Job Description

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) 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. Dropbox takes a number of factors into account when determining individual starting pay, including job and level they are hired into, location/metropolitan area, skillset, and peer compensation. We target most new hire offers between the minimum up to the middle of the range. 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): • US Zone 1: $233,800 - $275,000 - $316,300. • US Zone 2: $210,400 - $247,500 - $284,600. • US Zone 3: $187,000 - $220,000 - $253,000. Dropbox uses the zip code of an employee’s remote work location to determine which metropolitan pay range we use. Current US Zone locations are as follows: • US Zone 1: San Francisco metro, New York City metro, or Seattle metro • US Zone 2: Austin (TX) metro, Chicago metro, California (outside SF metro), Colorado, Connecticut (outside NYC metro), Delaware, Massachusetts, New Hampshire, New York (outside NYC metro), Oregon, Pennsylvania (outside NYC or DC metro), Washington (outside Seattle metro), Washington DC metro and West Virginia (DC metro) • US Zone 3: All other US locationsPandoLogic. Category:Technology, Keywords:Machine Learning Engineer, Location:Austin, TX-78758

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