Vice President, Machine Learning Engineering

Company: SiriusXM
Location: New York, New York, United States
Type: Full-time
Posted: 13.AUG.2021

Summary

DescriptionSiriusXM and Pandora have joined together to create the leading audio entertainment company in the U.S. Together, we are uniquely...

Description

DescriptionSiriusXM and Pandora have joined together to create the leading audio entertainment company in the U.S. Together, we are uniquely positioned to lead a new era of audio entertainment by delivering the most compelling subscription and ad-supported audio experiences to millions of listeners in the car, at home and on the go. Our talent, content, technology and innovation continue to be at the forefront, and we want you to be a part of it! Check out our current openings below and at Summary:The VP of Machine Learning Engineering is a hands-on leader tasked with managing the Information Technology ecosystem running our enterprise machine learning models at SiriusXM. The ecosystem includes, but is not limited to, the intricacies involved in operationalizing and scaling ML infrastructure and models across the company, powering the ML development lifecycle, and ensuring our ML technology and platforms are capable, scalable, efficient and reliable.In addition, this role will be an influencer and innovator to continue leveraging the use and adoption of machine learning across multiple business initiatives to achieve our most critical corporate objectives. Working collaboratively with members of the technology, analytics and business community across all SiriusXM enterprise functions, this role will leverage software engineering principles, analytical and data science knowledge, DevOps and data engineering principles in order to assist, innovate, govern, productionize and deploy machine learning, as well as to ensure we have an ethical and sustainable AI practice across the enterprise.Duties and Responsibilities:This role will lead the following functions within the Enterprise Data Office:Ensure Machine Learning Can Work at Scale and in Production at SiriusXMWork with Data Engineering to create reliable and reproducible data pipelines to ensure models are well fueledKeep innovating and optimizing the machine learning workflow, from data exploration, model experimentation/prototyping to production deployment, monitoring and performance tuning.Lead, monitor and oversee cost management for ML cloud-based technologies and servicesScale ML model performance, debugging and monitoring ML applications and tuning pipelinesDesign and implement machine learning life cycle managementProcess engineer and re-engineering to optimize and ensure SiriusXM can address challenges that may occur when integrating our models into workflows, applications and/or systems.Lead the adoption, use and governance of common tools and techniques to build large-scale AI applications, including productionizing models with CI and CDManage and Oversee the SiriusXM Enterprise ML Technology StackArchitect and maintain SiriusXM's enterprise Machine Learning ecosystem and sustainable infrastructure to serve the needs of our Data Scientist community; support our data-driven business activities at large scale.Perform R on new technologies and solutions to improve accessibility, scalability, efficiency and abilities of machine learning and analytics platformsProvide guidance, governance, self-service adoption strategies and oversight for a variety of tools and libraries that are used in both data science and machine learning. These include everything from ML libraries to deployment tools.Optimize efficiency of machine learning algorithms by applying state-of-the-art technologies, i.e. distributed computing, concurrent programming, or GPU parallel computing.Manage and govern Enterprise Python Data Science Tools and libraries, engineering tools and libraries, engineering tools including continuous integration, version control including logging, testing, and debugging and Enterprise ML deployment toolsInfluence, Guide and Assist with ML/AI Innovation to Achieve Business Goals & ObjectivesUnderstand the business applications and outcomes that can be achieved with ML/AI; Interpret the voice of the business as well as our customers to assist data scientists, data engineers, business intelligence analysts and our enterprise analytic community.Craft our ML/AI journey, from strategy and capabilities to execution and organization.Gain an understanding of our business model and framework to continue identifying use cases for AI across the customer journeyAssist with new opportunities across Broadcast Operations, Product, Marketing, Finance, Media and Information TechnologyInfluence how ML/AI can be used to create demand, enable ad sales, and support our direct sales organization with predictive and prescriptive intelligenceCollaborate with Analytics, Research and Insights team on how to optimize, improve and create action plans as we continue to leverage our data and understand deeper customer segments, conversion rate optimization, and customer churn opportunitiesNavigate the black box and ethical considerations of Artificial Intelligence to drive responsible AI initiatives.Be an active influencer in our analytics community of like-minded professionals who are successfully deploying advanced analytics, ML and AI in their business functions.Establish a strong collaborative culture with peers and other functions within SiriusXM. Promote a culture of success, pride, performance, discipline, innovation and creativity.Minimum Qualifications:Master's degree in Computer Science, Statistics, Engineering or a related fieldExpertise in Machine Learning techniques applied to real-time decisioning systemsStrong track record of full lifecycle product development (build/run)10+ years of total experience in a software-related field.5+ years in a technical leadership role with direct oversight and team supervision; Experience leading teams that adopt DevOps & MLOps strongly preferred5+ years in software engineering or related experience designing distributed systems at scale3+ years of technology forecast planning & budget management/spending; cloud cost management & cost optimization experience a strong plusAbility to partner closely with a diverse set of business partners to identify needs and deliver solutionsAbility to gather and analyze large amounts of information expeditiously. Develop compelling and insightful recommendations to inform strategic research decisions by leaders and teams.Ability to improve the diversity of thought of the broader analytics community through background and/or experienceProven expertise synthesizing and presenting research/technical findings to diverse audiencesAdvance skills in algorithm development and predictive modelingExperience designing and implementing reliable and high availability solutions for training, inferencing stages of production models, online and offline ML systems.Requirements and General Skills:Experience speaking in large and high visibility forums; demonstrable experience building relationships and communicating complex topics simply to the organizationInterpersonal skills and ability to interact and work with staff at all levels.Excellent written and verbal communication skills.Ability to work independently and in a team environment.Ability to pay attention to details and be organized.Ability to project professionalism over the phone and in person.Ability to handle multiple tasks in a fast-paced environment.Commitment to "internal client" and customer service principles.Willingness to take initiative and to follow through on projects.Spelling, grammar, proofreading and editing skills.Creative writing ability.Excellent time management skills, with the ability to prioritize and multi-task, and work under shifting deadlines in a fast-paced environment.Must have legal right to work in the U.S.Technical Skills:Experience developing data pipelines, and orchestrating deployment of ML models, including experience with KubernetesFamiliarity with ML model development frameworks, ML orchestration and pipelines with experience in either Knime, Airflow, Kubeflow or MLFlowStrong understanding of containerization (Docker, etc.), and associated software engineering best practicesUnderstanding of machine learning algorithms, such as k-NN, GBM, Neural Networks Naive Bayes, SVM, and Decision Forests.Practical experience with ML platforms such as Tensorflow/Keras, PyTorch, etc.Understanding of NoSQL (Graph, Document, Columnar) database models, XML, relational and other database models and associated SQL;Understanding of ETL tools and techniques, such as tools like Talend, Informatica, etc.; knowledge of how to map transformation and flow of data from a source to a target systemExtensive experience in development language environments-e.g. Python, Java, Scala, C+, R, SQL, etc. and applying analytical methods to large and complex datasets leveraging one of those languagesPractical experience with statistical data analysis and experimental designDeep knowledge of Cloud platforms (AWS/GCP preferred; Prior experience of AWS Sage Maker would be an added advantage.Expertise in one or more specialized areas; e.g., deep learning (DL), reinforcement learning (RL), planning, information representation and retrieval, graphs, multi-agent systems (MAS), computational game theory, natural language processing (NLP)More details about our company benefits can be found here!Our goal at SiriusXM+Pandora is to provide and maintain a work environment that fosters mutual respect, professionalism and cooperation. SiriusXM+Pandora is an equal opportunity employer that does not discriminate on the basis of actual or perceived race, creed, color, religion, national origin, ancestry, alienage or citizenship status, age, disability or handicap, sex, gender identity, marital status, familial status, veteran status, sexual orientation or any other characteristic protected by applicable federal, state or local laws.The requirements and duties described above may be modified or waived by the Company in its sole discretion without notice.

 
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