Machine Learning Engineer, Platform & Data

Changing the world through digital experiences is what Adobe's all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences!
$135,200 - $250,900
Machine Learning
Mid-Level Software Engineer
In-Person
3+ years of experience
AI

Description For Machine Learning Engineer, Platform & Data

Firefly is the new family of creative generative AI models coming to Adobe products that offers a new way to conceptualize, build, and scale content. It's a natural extension of the technology Adobe has produced over the past 40 years. At the core of Firefly are our commercially safe AI models trained on hundreds of millions of images owned or licensed by Adobe. We are hiring for a highly strategic and visible role to help evolve these models. This is an opportunity to reach millions of creatives, helping them reinvent the way they work.

Responsibilities: • Design, architect and build cloud ML platform solutions related but not limited to resource management, monitoring, allocation, and job scheduling. • Design, architect and build reliability, observability and utilization infrastructure for cloud computing resources. • Collaborate with data platform engineers and architects to seamlessly integrate low latency data pipelines into the ML platform for model training. • Collaborate with machine learning and data scientists to identify and resolve requirements in order to improve the training cost and turnaround time on the ML platform. • Monitor machine learning platform performance and modify infrastructure to fit fluid cloud resource needs. • Write high quality, product level code that is easy to maintain and test following standard methodologies.

Key skill requirements: • Proficiency in at least two of: Linux, Ansible, Docker, Kubernetes (3+ yrs) • Expert in Python and or C++ • Experience in distributed computing (3+ yrs) • Experience in HDFS, Spark, Presto (3+ yrs) • Experience working with AWS or similar cloud infrastructure (3+ yrs) • Experience with HW resource management for ML training and/or deployment • B.S., M.S, or Ph.D. in Computer Science, Computer Engineering or a related area

Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this position is $135,200 -- $250,900 annually. Pay within this range varies by work location and may also depend on job-related knowledge, skills, and experience. Your recruiter can share more about the specific salary range for the job location during the hiring process.

At Adobe, for sales roles starting salaries are expressed as total target compensation (TTC = base + commission), and short-term incentives are in the form of sales commission plans. Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP).

In addition, certain roles may be eligible for long-term incentives in the form of a new hire equity award.

Adobe will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and "fair chance" ordinances.

Last updated 2 months ago

Responsibilities For Machine Learning Engineer, Platform & Data

  • Design, architect and build cloud ML platform solutions related but not limited to resource management, monitoring, allocation, and job scheduling
  • Design, architect and build reliability, observability and utilization infrastructure for cloud computing resources
  • Collaborate with data platform engineers and architects to seamlessly integrate low latency data pipelines into the ML platform for model training
  • Collaborate with machine learning and data scientists to identify and resolve requirements in order to improve the training cost and turnaround time on the ML platform
  • Monitor machine learning platform performance and modify infrastructure to fit fluid cloud resource needs
  • Write high quality, product level code that is easy to maintain and test following standard methodologies

Requirements For Machine Learning Engineer, Platform & Data

Python
Linux
Kubernetes
  • Proficiency in at least two of: Linux, Ansible, Docker, Kubernetes (3+ yrs)
  • Expert in Python and or C++
  • Experience in distributed computing (3+ yrs)
  • Experience in HDFS, Spark, Presto (3+ yrs)
  • Experience working with AWS or similar cloud infrastructure (3+ yrs)
  • Experience with HW resource management for ML training and/or deployment
  • B.S., M.S, or Ph.D. in Computer Science, Computer Engineering or a related area

Benefits For Machine Learning Engineer, Platform & Data

  • 401k
  • Equity

Interested in this job?

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