Computer Scientist-II

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!

The Challenge:

As part of the Machine Learning and Optimization team in the Adobe Advertising Cloud, you will be working on cutting edge research to help advertisers maximize revenue and increase brand awareness on Adobe's DSP (Demand Side Platform) with 100s billions of auctions per day. You will help build the next generation of predictive models and optimization algorithms that power the RTB (real time bidding) platform that are used by hundreds of clients across the world in a fast paced environment.

What will you do:

• Develop classifiers, predictive models and multi variate optimization algorithms on large-scale datasets using advanced statistical modeling, machine learning and data mining.

• Design and implement scalable models that can work with large-scale datasets (100s billions of records) in production systems

• Ability to articulate the design and implementation choices to cross functional teams

• R&D will revolve around a few key focus areas such as predictive models for conversion optimization, Bidding algorithms for pacing & optimization, Reinforcement learning problems and Forecasting.

What you require:
• 5-10yrs. of Total experience with relevant experience of 5yrs. as Data Engineer(primary), as ML engineer(secondary).

• Solid foundation in machine learning, NLP, classifiers, statistical modeling and multivariate optimization techniques

• Experience with control systems, reinforcement learning problems, contextual bandit algos.

• Experience with DNN frameworks like TensorFlow or PyTorch on large scale data sets.

• TensorFlow, R, scikit, pandas

• Proficient in one or more: Python, Java/Scala, SQL, Hive, Spark

• Good to have - Git, Bazel, Docker, Kubernetes

• General understanding of data structures, algorithms, multi-threaded programming and distributed computing concepts

• Ability to be a self starter and work closely with other data scientists and software engineers to design, test and build production ready ML and optimization models and distributed algorithms running on large scale data sets

• Strong analytical, quantitative problem solving, and communication skills

• Proven ability to work well in a high performing team with agile development approaches and technology

Ideal Candidate Profile:

• PHD (with 3+years experience) or Masters (with 5+ years experience) in Computer Science/Electrical Engineering/Statistics or relevant field

• Experience with Real Time Bidding / Ad Tech background preferred

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