AI/ ML Lead Architect

Key Skills

Aartificial intelligence, Apache Hadoop, Java Programming, Keras software library, Machine learning techniques, Natural Language Processing (NLP), NumPy, Pandas, Python Programming, PyTorch, Scikit-learn, SciPy, Spark Core, TensorFlow

Job Description

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!

Digital Learning group at Adobe is looking for an expert in Machine Learning to deliver modern and innovative experiences to our customers across a set of products in Learning domain. You will lead all the processes from data collection, cleaning, and pre-processing, to training models and deploying them to production. The ideal candidate will be passionate about AI/ML and stay up-to-date with the latest developments in the field. 

What will you do:

• Develop search and recommendation system leveraging semantic understanding, text classification, reputation and ranking models
• Understanding business objectives, develop models that help achieve them, along with metrics to track progress.
• Articulate the design and implementation choices to cross functional teams
• Develop pipelines to monitor, extract, index, build and tune ML and NLP models

What you need to succeed:

• 5+ years’ hands-on experience in Recommendation Systems, Natural Language Processing, Information retrieval, and Deep Learning.
• A track record of delivery within several large-scale projects, demonstrating ownership of machine learning models and architecture solutions.
• Proficiency with one or more state-of-art deep learning frameworks, such as Tensorflow, PyTorch, Keras, Caffe, Torch on large scale data sets.
• Proficient in Python or Java, Basic machine learning libraries like Pandas, Numpy, Scikit-learn, SciPy, Gensim, Glove
• Proficiency with distributed computational frameworks (YARN, Spark, Hadoop)
• General understanding of data structures, algorithms, multi-threaded programming and distributed computing concepts.
• Ability to be a self-starter and work closely with other product, data scientists and software engineers to design, test and build production ready ML models.
• MS/MTech/B.Tech in Computer Science