Senior ML Engineer

Job-Zusammenfassung:

At Disney, we’re storytellers. We make the impossible, possible. The Walt Disney Company is a world-class entertainment and technological leader. Walt’s passion was to continuously envision new ways to move audiences around the world—a passion that remains our touchstone in an enterprise that stretches from theme parks, resorts and a cruise line to sports, news, movies and a variety of other businesses. Uniting each endeavor is a commitment to creating and delivering unforgettable experiences — and we’re constantly looking for new ways to enhance these exciting experiences.

The Enterprise Technology mission is to deliver technology solutions that align to business strategies while enabling enterprise efficiency and promoting cross-company collaborative innovation. Our group drives competitive advantage by enhancing our consumer experiences, enabling business growth, and advancing operational excellence.

The Enterprise Cloud Data & Analytics team is part of the Cloud Data and Transformation Engineering team. The team’s primary function is to provide curated datasets to support business decisions and to help provide insights for the TWDC enterprise cloud spend and usage. Processes supported include monthly supplier invoice validation, monthly internal chargeback, forecasting, cost optimization, etc.

We apply best data engineering and business intelligence practices to data sources to generate business insights in the form of curated data. We also maintain the data system that supports secure, on-demand consumption of data by our internal consumers.

What You Will Do

• Build ML Models

• Build data pipelines, cleanse data, train models and inference predictive models to forecast.

• Work closely with Product, Stakeholders, engineering groups to understand requirements and build hypothesis. 

• Run experiments to prove hypothesis or create PoCs for different ML use cases.

• Work with different algorithms and ML problem domains such as Forecasting, NLP, LLM, Regression and Classification.

• Present results of experiments in a consumable fashion write ups/PPTs to VPs and other executives.

• Monitor model performance and retrain models where necessary.

• Follow MLOps best practices.

Responsibilities: 

• Experience with frameworks and libraries for machine learning & AI such as scikit-learn PyTorch, Tensorflow/Keras, MLlib, etc.

• Develop and maintain automated data solutions that ingest, transform and generate insights in the form of curated datasets.

• Experience in building, deploying and managing forecasting models for time series datasets.

• Experience with building batch and streaming pipelines using complex SQL, PySpark, and similar frameworks

• Support and maintain the shared consumer data platform with regard to data organization, access, security and role appropriate access.

• Analyze and model data to design data solutions that provide business insights.

• Recognizing patterns and opportunities to consolidate implementations and/or create standards

• Collaborate with engineers, product managers, and data scientists to understand data needs, representing key data insights in a meaningful way.

• Optimize pipelines, dashboards, frameworks, and systems to facilitate easier development of data artifacts

• Have a growth mindset and a desire to learn

• Mentor team members by giving them actionable feedback

• Be proactive and have initiative

• Provide clear and concise communication to technical and non-technical audiences

Preferred Qualifications:

• A minimum of 5 years of related work experience

• Experience in running high quality data pipelines

• Experience in Python, SQL, ETL, Data Analysis and data modeling and designing a data architecture.

• Experience in Databricks, and building, managing and optimizing Spark jobs

• Experience in AWS and Azure Cloud

 Nice To Haves:  

• Databricks certification

• Understanding of Financial operations and Finops

• Good understanding of Large Language Models (LLMs).

Education:

• Bachelor’s degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience

The hiring range for this position in Seattle, WA is $142,600 to $191,100. The base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.