Adobe Company logo on Dataaxy
Adobe

Machine Learning Engineer

📍
San Francisco, CA
🧪
Entry level
Our Company

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! We’re passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen.

We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours!

What you will do :

  • Collaborate with data platform engineers and architects to seamlessly integrate low latency data pipelines into the ML platform for model training.
  • Write high quality, product level code that is easy to maintain and test following standard methodologies.
  • Design and implement reusable and scalable data loading framework that supports video and audio foundational model training in large-scale and distributed environments.
  • Collaborate closely with ML Researchers and Machine Learning engineers to accelerate the training of the cutting-edge ML models.
  • Keep track of the latest innovation in academia and open-source community to implement rapid adoption of pioneering technologies to improve the performance of the ML platform.

What you'll need to succeed:

  • B.S., M.S, or Ph.D. in Computer Science, Computer Engineering, Statistics, Mathematics, Physics or a related area
  • Strong fundamentals in Machine Learning / Computer Vision / Natural Language Processing
  • Experience building machine learning models in a product environment
  • Experience in data processing and scientific computing tools such as NumPy and Pandas
  • Experience with Machine Learning / Deep Learning frameworks such as Scikit Learn, TensorFlow, Pytorch
  • Excellent communication skills and growing mindset

#FireflyGenAI

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 is proud to be an Equal Employment Opportunity and affirmative action employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other applicable characteristics protected by law. Learn more.

Adobe aims to make Adobe.com accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodations@adobe.com or call (408) 536-3015.

Adobe values a free and open marketplace for all employees and has policies in place to ensure that we do not enter into illegal agreements with other companies to not recruit or hire each other’s employees.

Key informations

🧳
Full-time
📅
Posted 9 months ago

Don’t miss out on new
Data & AI Jobs

Get curated job alerts weekly.

Other jobs at Adobe

Adobe does not currently have any open job positions in Data & Ai.
© 2023 | All Rights Reserved | Built with 🤍 in MontrealAll our data is gathered from publicly available sources or contributed by users