Lead Platform Engineer - Machine Learning
Lake Buena Vista, FL - USApply Now Apply Later
Job ID 712893BR Location Lake Buena Vista, Florida, United States; Orlando, Florida, United States Business Parks, Experiences and Products Date posted 16/10/2019
The Lead Machine Learning Platform Engineer spearheads development and operationalization of key framework components required in the end-to-end machine leaning lifecycle. Using these building blocks, Parks Data and Machine Learning Platform (“the platform”) supports 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 developers, data engineers, data scientists, content creators and business analysts across the entire Disney Parks Experiences and Products (DPEP) organization to build, deploy, sustain and continuously improve AI services.
- Lead a team of engineers to design and develop production grade frameworks for feature engineering, model architecture selection, model training, model interpretability, A/B testing, containerization, deployment and feedback.
- Introduce MLOps tools in conjunction with the existing DataOps and DevOps tools in the platform to facilitate collaboration across diverse user groups within the organization.
- Create automated self-service procedures that allow the platform to scale across multiple agile projects with minimal overhead.
- Define SLAs for provisioning and supporting the ML platform services.
- Integrate tools for optimizing human resource allocation in tasks involving varying degrees of complexity such as labeling, modelling, puppeting.
- Enforce effective cost optimization techniques in cloud, on-prem, and edge environments to minimize the total cost of ownership of the AI services.
- Integrate tools for measuring model KPIs, data deviation and drift.
- Provide bootstrapping templates for the frequently used ML algorithms and pipelines.
- Build reference implementations to demonstrate use of the platform.
- Guide delivery studios with accuracy-cost-explainability tradeoffs; create tools to measure them.
- Create environment of accountable, auditable, reproduceable and ethical AI by providing tools and guidance to business partners.
- Continually scan the industry and academia for new tools and methods in machine learning. Assist in defining the roadmap and evolution of the platform.
- Participate in formal/informal discussion forums to simplify and evangelize AI/ML.
- 3+ years of experience in training, tuning, deploying, and operationalizing ML models.
- 5+ years of experience in software development in an agile environment.
- 2+ years of experience in building infrastructure-as-a-code services
- 2+ years of experience in developing reusable frameworks.
- Expert level knowledge of deep learning frameworks such as TensorFlow, MXNet, Pytorch etc.
- Expert in native AWS big data stack - S3, Glue, EMR, Sagemaker, Kinesis, Lambda, DynamoDB etc.
- Working knowledge of infrastructure-as-a-code using Cloudformation or Terraform
- Working knowledge of ML model architectures and hyper-parameter tuning.
- Working knowledge of Clustering, CNN, RNN, RL and LSTM
- Working knowledge of libraries such as scikit-learn, keras, pandas, svm, xgboost etc.
- Hands-on experience with ML lifecycle tools such as AWS Sagemaker, MLflow, TensorFlow Serve etc.
- Hands-on experience with coding, troubleshooting and performance tuning ML pipeline involving large datasets in a collaborative project environment.
- Working knowledge of Apache big data stack – Spark, Yarn, Oozie, Kafka etc.
- Experience in using 3rd party computer vision algorithms (e.g OpenCV) and video processing libraries (e.g. NVIDIA DeepStream)
- Knowledge of various media formats, encoding schemes and streaming protocols for computer vision ML pipeline.
- Knowledge of various relational/non-relational databases and storage technologies.
- Knowledge of high performance databases and caching solutions (e.g. Redis)
- Experience in accelerating deep learning frameworks using GPU and micro-batching
- Familiarity with ongoing research in model explanability; theoretical knowledge of techniques such as LRP, CEM, LIME.
- Master’s Degree in Computer Science, Distributed Computing, Machine Learning, Mathematics or related field
About Parks, Experiences and Products:
The Parks, Experiences and Products segment includes Disney’s iconic travel and leisure businesses, which include six resort destinations in the United States, Europe and Asia, a top-rated cruise line, a popular vacation ownership program, and an award-winning guided family adventure business. Disney’s global consumer products operations include the world’s leading licensing business across toys, apparel, home goods, digital games and apps; the world’s largest children’s publisher; Disney store locations around the world; and the shopDisney e-commerce platform.
About The Walt Disney Company:
The Walt Disney Company, together with its subsidiaries and affiliates, is a leading diversified international family entertainment and media enterprise with the following business segments: media networks, parks and resorts, studio entertainment, consumer products and interactive media. From humble beginnings as a cartoon studio in the 1920s to its preeminent name in the entertainment industry today, Disney proudly continues its legacy of creating world-class stories and experiences for every member of the family. Disney’s stories, characters and experiences reach consumers and guests from every corner of the globe. With operations in more than 40 countries, our employees and cast members work together to create entertainment experiences that are both universally and locally cherished.
This position is with Walt Disney Attractions Technology LLC, which is part of a business segment we call Parks, Experiences and Products.
Walt Disney Attractions Technology LLC is an equal opportunity employer. Applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Disney fosters a business culture where ideas and decisions from all people help us grow, innovate, create the best stories and be relevant in a rapidly changing world.
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