Senior Computer Scientist

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

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 you’ll do

• Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress
• We are looking for results-oriented machine learning engineer. The work spans modelling, data engineering, model optimization, large scale experimentation, and shipment of cutting edge technology
• Develop pipelines to monitor, extract, index and build & tune ML & NLP models
• Managing available resources such as hardware, data, and personnel so that deadlines are met
• Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world
• Verifying data quality, and/or ensuring it via data cleaning
• Supervising the data acquisition process if more data is needed
• Finding available datasets online that could be used for training
• Defining validation strategies
• Defining the pre-processing or feature engineering to be done on a given dataset
• Defining data augmentation pipelines
• Training models and tuning their hyperparameters
• Analysing the errors of the model and designing strategies to overcome them
• Deploying models to production. Converting the AI models into microservices and deploy them using dockers.
• Proficiency with a deep learning frameworks especially TensorFlow, Pytorch and Keras. 
• Proficiency with distributed computational frameworks (YARN, Spark, Hadoop)
• Proficiency with Python and basic libraries for machine learning such as Scikit-learn, Pandas, SciPy, Gensim and Numpy
• Expertise in visualizing and manipulating big datasets
• Familiarity with Linux
• Working proficiency with SQL and relational databases, data warehouse.
• Experience with GPU/CUDA for computational efficiency.
• Good exposure in exploratory data analysis
• Ability to select hardware to run an ML model with the required latency
• Develop pipelines to monitor, extract, index and build & tune ML & NLP models

What you need to succeed

• 8+ years’ experience in the areas of machine learning which includes Deep learning, Natural Language Processing, Computer vision, Information retrieval, Data mining & Distributed systems and Recommender systems.
• A track record of delivery within several large-scale projects, demonstrating ownership of machine learning models and architecture solutions.