Role Details:

Curiosity about applying machine learning e.g, supervised methods like SVMs, random forests, deep learning & reinforcement learning, to existing products and services to improve their efficiency and the overall user experience across our digital properties. Leverage datasets like traffic/video/ consumption data from Adobe Analytics, purchase/subscription data, and third-party data sources, to model, analyze and predict user behavior. Take ownership of machine learning products from conception through delivery and monitoring.

Your Day-to-Day:

• Craft and develop highly scalable and reliable machine learning solutions to improve user experience.
• Overcome engineering challenges with deploying machine learning solutions at scale.
• Investigate new ways machine learning can improve products and determine viability of solutions.
• Keep up with machine learning research and commercial product offerings across a wide variety of machine learning fields including NLP, recommendations, image, and video.
• Participate in design and code reviews.
• Effective communication is essential as this is a distributed team.

Key Projects:

• Pioneer new product ideas for how machine learning can improve products and take ownership from inception through implementation.
• Deliver recommendations across Paramount and PlutoTV platforms that serve millions of customers daily.
• Work on state-of-the-art video solutions applying machine learning to both live streaming video and VOD.
• Curate our content platform to design and develop sophisticated products to collect, transform and enrich data in a fast, scalable, and reliable way for ourselves and our customers.

Basic Qualifications:

• 2-3 Years of proven experience bringing machine learning software products to production.
• Leads on design and optimization of ML pipelines and developer experience.
• MA/MS in Statistics/Data Science/Computer Science or related quantitative disciplines with specialization in data mining or machine learning techniques.
• Knowledge of both supervised and unsupervised machine learning techniques in major types of approaches that they should be familiar with LTR (Learning to rank), Transformer Architectures, Sequences models for offline and online inference.
• Have full stack experience in data collection, aggregation, analysis, visualization, productionalization, and monitoring of data science products.
• Kubernetes - must know basics, APIs - good working knowledge, Message Queues (PubSub) - good working knowledge, and distributed processing like Ray and large DBs like BigQuery.
• Proficiency in Python and associated machine learning packages is a must Python, Tensorflow and/or PyTorch, (tensorflow preferred), experience with a Python web framework (Django/Flask) is preferred.
• SQL skills Nice to have Go or Java experience.
• Communicate concisely and persuasively with engineers and product managers.

Additional Qualifications:

• Experience with Tensorflow Extended (TFX), KubeFlow and related tools.
• Experience using project management tools like those from Atlassian (JIRA, Confluence).
• Familiarity with version control systems (Git and Bitbucket).
• Experience using Google Cloud Platform (BigQuery, ML Engine, and APIs).
• Background in NLP or text mining techniques is a plus.
• Background in deep learning is a plus.
• Familiarity with Kubernetes and cloud deployments.
• Experience with elasticsearch.
• Desire to contribute to the open-source community (i.e., blogs, source code, etc).