Machine Learning - Technology Manager

Key Skills

SQL, Python Programming, R Programming, AWS, Tableau, Scala Programming

Job Description

“We make magic.” That’s our motto at Disney Parks, Experiences and Products (DPEP). And it permeates everything we do. At Disney, you’ll help inspire that magic by enabling our teams to push the limits of entertainment and create the never-before-seen!
Data Science and Engineering group within DPEP spearheads cutting edge data and AI capabilities to create magical guest experiences and unparalleled operational efficiencies. As the Manager of the MLOps platform, you will lead a technology team to build and operationalize end-to-end Machine Learning platform supporting a wide variety of applications in computer vision, natural language processing, data analytics, predictions, recommendations, content creation and optimization. The platform enables multiple studios of app developers, data engineers, data scientists, content creators and business analysts to build, deploy, sustain and continuously improve AI services.

Responsibilities:

• Lead and mentor a team of engineers to design and develop production grade frameworks for data discovery, feature engineering, feature caching, architecture selection, model training, model interpretability, A/B testing, containerization, deployment and feedback.
• Achieve operational excellence through disciplined engineering and metric driven governance.
• Create a culture of incessant automation.
• Introduce MLOps tools in conjunction with the existing DataOps and DevOps.
• Create automated self-service procedures that allow the platform to scale across multiple agile projects.
• Manage SLAs for provisioning, high availability and scalability of the platform.
• Operationalize productivity tools to take advantage of “right sourcing” diverse ML tasks such as data labeling, wrangling, modelling, puppeting(M Turk) etc.
• Operationalize creative ways to optimize the total cost of ownership of AI services in cloud, on-prem, and on-edge environments.
• Operationalize instrumentation for measuring model KPIs, drift and cost functions.
• Build proof-of concepts and reference implementations to demonstrate the use of the platform.
• Guide application studios on accuracy-cost-interpretability tradeoffs; create tools to measure them.
• Foster an environment of explainable, accountable, auditable, reproduceable and ethical AI.
• Stay abreast of the academic and industrial trends in AI, Machine Learning and Distributed Computing. Assist in defining the roadmap and evolution of the platform.
• Participate in formal/informal forums to simplify and evangelize AI/ML.

Basic Qualifications:

• 3+ years of technology leadership experience in a data/analytics/innovation team.
• 3+ years of experience in training, tuning, deploying, and operationalizing ML models.
• 5+ years of experience in software development in an agile environment.
• 3+ years of experience in building technology platforms.
• Solid experience as a leader and a coach, with ability to build and organize teams.
• Expert in native AWS AI/ML stack - S3, Glue, EMR, Sagemaker, Kinesis, Lambda, DynamoDB, Rekognition etc.
• Expertise in troubleshooting performance issues and rallying teams to a timely resolution.
• Working knowledge of infrastructure-as-a-code and automation tools such as AWS CDK, Ansible, Chef.
• Working knowledge of various ML model architectures and hyper-parameter tuning.
• Familiarity with coding, troubleshooting and performance-tuning ML pipeline involving large datasets in a collaborative project environment.
• Understanding of data governance, security and privacy laws.

Preferred Qualifications:

• Experience of wearing multiple hats (management, architecture and engineering) in a start-up environment.
• Familiarity with Google and Azure cloud platforms.
• Familiarity with Apache big data stack – HDFS, Hive, Spark, Yarn, Kafka etc.
• Familiarity with ongoing research in model explanability; theoretical knowledge of techniques such as LRP, CEM, LIME.

Please note that this is an engineering management role and not a data scientist role. The ideal candidate should be able to multi-task across various development, operations, analytical and administrative tasks.

Required Education

• Bachelor’s Degree in Computer Science, Distributed Computing, Information Systems or equivalent work experience.