Machine Learning Engineer
1 month ago
Job Description
Excited by AI/ML? We are looking for a talented individual to join our Document Cloud team to create innovative solutions using Machine Learning.
The team is working on PDF solutions spanning all surfaces - Web, Mobile, Desktop and Platform APIs, that processes billions of PDFs every month using ML, Deep-Learning and Generative AI at its core.
As a part of this, we need experienced individuals focusing on research and development of methods for processing huge amount of content, and can build mashups of Vision, Image Processing, NLP, generative models to solve complex problems.
Key Responsibilities:
- Develop algorithms that apply deep learning and state of the art methods in NLP & computer vision, combined with traditional large sophisticated solutions/codebases.
- Create experiments, algorithms and ship solution that not only yield high accuracy but are also designed and engineered to scale.
- Collaborate across multiple research and engineering disciplines, making the tradeoffs required to rapidly deliver AI/ML software solutions.
Requirements:
- B. Tech / MCA in Computer Science or related fields. MS/PhD preferred.
- 5 - 8 years hands-on experience in either deep-learning models, Image processing, Vision and/or NLP.
- Ability to write efficient, clean, and reusable code in Python. Knowledge of C++ is preferred.
- Broad Machine Learning experience – Data, Modelling, Metric, Analysis of Results.
- Experience in using TensorFlow or PyTorch.
- Exposure to Deep Learning - CNNs, LSTMs, Transformers, network architecture, network tuning, transfer learning, multi-task learning.
- Exposure in building solutions from scratch and writing maintainable code inside large existing codebases.
- Strong software development skills that encourage code reuse among engineers and researchers.
Why Adobe?
At Adobe, you will be immersed in an exceptional work environment that is recognized throughout the world. You will also be surrounded by colleagues who are committed to helping each other grow through our unique approach where ongoing feedback flows freely.
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