Staff Infrastructure Software Engineer, ML Platform
Role Description
As a Staff Software Engineer joining our Machine Learning platform team, you will shape the Machine Learning foundation for Dropbox.
In this role, you will be crucial in architecting and developing reliable and performant software infrastructure that enables our customers to build high impact ML solutions at scale. You will work closely with machine learning engineers and data scientists to develop and maintain new systems and tooling, accelerating their ML development velocity and providing great and unified user experiences throughout the whole ML lifecycle.
We care deeply about collaboration, feedback, and iteration. Trust and respect are deeply rooted in our engineering culture. We're bold when it comes to shipping high-leverage projects, even if they're risky or novel. We hope you'll join us!
Responsibilities
- You will identify and lead strategic initiatives that streamline ML Operations (MLOps), optimize platform performance, and improve system health
- You will design, build, test and maintain scalable and reliable infrastructure that supports machine learning workflows from training to serving ML models
- You will provide technical leadership and guidance to engineers and multi-functional partners
- You will collaborate with cross-functional teams to understand their requirements and develop solutions that meet their needs
Requirements
- BS, MS, or PhD in Computer Science or related technical field involving coding (e.g., physics or mathematics), or equivalent technical experience
- 15+ years of professional software development experience
- Extensive experience building and owning large-scale, multi-threaded, geographically distributed backend systems
- Experience with ML infrastructure
- Highly skilled at developing and debugging in C/C++, Java, or Go, with knowledge of Python a plus
- Strong communication skills and ability to work effectively in a collaborative team environment
- Familiarity with relevant technology stacks a plus (ie. AWS, Kubernetes, Docker, Kubeflow, Ray, Tensorflow, PyTorch)
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.
For candidates hired in San Francisco metro, New York City metro, or Seattle metro, the expected salary/On-Target Earnings (OTE) range for the role is currently $229,500 - $270,000 - $310,500.
For candidates hired in the following locations: 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) and Washington DC metro, the expected salary/On-Target Earnings (OTE) range for the role is currently $206,600 - $243,000 - $279,500.
For candidates hired in all other US locations, the expected salary/On-Target Earnings (OTE) range for this role is currently $183,600 - $216,000 - $248,400.
Range(s) is subject to change. 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. Dropbox uses the zip code of an employee’s remote work location to determine which metropolitan pay range we use.
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).
