Staff Applied Scientist
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Role Description
We are looking for a machine learning leader to build the AI systems that will drive Dropbox’s new initiatives. This will involve driving the design, development, and execution of scientific research projects using modeling, simulation, and optimization to design processes, algorithms, and prediction/classification systems. This work will supports multiple products which touch hundreds of millions of people and a *lot* of data. These AI/ML systems will power Dropbox services like Dash, Dropbox AI and more.
Models and system designs must handle complex use cases of privacy and drive real-world customer wins and business results while meeting Dropbox AI Principles.
Responsibilities
Understand large complex use cases across the business and design the model solution that is scalable, efficient, automated
Design, develop, and deploy highly innovative modeling techniques, in particular next generation of tools/features empowered by LLMs
Partner closely with other Dropbox scientists focused on LLM use cases
Drive and lead strategic initiatives to employ the most recent advances in ML/AI in a fast-paced, experimental environment impacting multiple products
Work closely with teams of scientists and software engineers to drive real-time model implementations and deliver novel and highly impactful features
Mentor and grow the scientists in the team and across Dropbox
Requirements
MS or PhD in Computer Science or related technical field, or equivalent technical experience
10+ years of experience building consumer or enterprise facing large scale ML/AI systems
Strong communication skills and a demonstrated passion for helping others leverage machine learning
Fluency in Python, SQL or similar scripting languages and skilled at Java, C++, or other programming languages.
Preferred Qualifications
Experience with large scale search systems
Experience building RAG systems
Experience with LLMs - finetuning, prompt engineering, etc.
Total Rewards
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: $210,800 - $248,000 - $285,200. • US Zone 2: $189,700 - $223,200 - $256,700. • US Zone 3: $168,600 - $198,400 - $228,200. 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 locations
Staff Applied Scientist
To see similar active jobs please follow this link: Remote Development jobs
Role Description
We are looking for a machine learning leader to build the AI systems that will drive Dropbox’s new initiatives. This will involve driving the design, development, and execution of scientific research projects using modeling, simulation, and optimization to design processes, algorithms, and prediction/classification systems. This work will supports multiple products which touch hundreds of millions of people and a *lot* of data. These AI/ML systems will power Dropbox services like Dash, Dropbox AI and more.
Models and system designs must handle complex use cases of privacy and drive real-world customer wins and business results while meeting Dropbox AI Principles.
Responsibilities
Understand large complex use cases across the business and design the model solution that is scalable, efficient, automated
Design, develop, and deploy highly innovative modeling techniques, in particular next generation of tools/features empowered by LLMs
Partner closely with other Dropbox scientists focused on LLM use cases
Drive and lead strategic initiatives to employ the most recent advances in ML/AI in a fast-paced, experimental environment impacting multiple products
Work closely with teams of scientists and software engineers to drive real-time model implementations and deliver novel and highly impactful features
Mentor and grow the scientists in the team and across Dropbox
Requirements
MS or PhD in Computer Science or related technical field, or equivalent technical experience
10+ years of experience building consumer or enterprise facing large scale ML/AI systems
Strong communication skills and a demonstrated passion for helping others leverage machine learning
Fluency in Python, SQL or similar scripting languages and skilled at Java, C++, or other programming languages.
Preferred Qualifications
Experience with large scale search systems
Experience building RAG systems
Experience with LLMs - finetuning, prompt engineering, etc.
Total Rewards
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: $210,800 - $248,000 - $285,200. • US Zone 2: $189,700 - $223,200 - $256,700. • US Zone 3: $168,600 - $198,400 - $228,200. 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 locations