Top Hybrid Data Engineer Jobs in Seattle, WA
Design, build, and enhance batch and real-time inference services and tooling to support Machine Learning use cases. Collaborate with cross-functional stakeholders to drive strategic roadmaps and priorities. Partner with ML modelers to encourage adoption of new tools and technologies. Have a significant impact on influencing team culture.
Design, implement, and scale critical machine learning components and services to support Snap's most strategic initiatives. Build a next-generation training framework, perform model training optimization, and develop an AutoML platform. Provide technical direction that influences the entire company.
Hiring Senior Machine Learning Engineers to join the ML Platform team at Warner Bros. Discovery. Responsible for building a scalable Machine Learning platform to train, evaluate, deploy, serve, and monitor ML models for global brands.
Featured Jobs
Architect and lead development of scalable machine learning systems, collaborate with team members to deploy and maintain models, evaluate new technologies, design software architecture, communicate with peers, value collaboration and innovation.
Senior Machine Learning Engineer specializing in data-driven attribution to fuel Square's growth. Responsible for building machine learning solutions for the next generation attribution system, collaborating with stakeholders, and staying updated on advancements in ML and data science.
Building, orchestrating, and monitoring model pipelines, scaling machine learning algorithms, enhancing ML Engineering platforms, implementing ML Ops, writing production-ready code, collaborating with teams, and staying updated on the latest technologies.
Senior Data Engineer role at Disney Entertainment & ESPN Technology's Data Platforms Team. Responsible for designing, building, and maintaining data pipelines in Scala, Python, and Spark. Collaborate with Data Product Managers, Architects, and Engineers to deliver data solutions and ensure operational efficiency. Strong technical background required for working with AWS, Databricks, Snowflake, Airflow, and more.
Develop new product features, explore emerging technologies, build and deploy machine learning models, work with large language models, create APIs and web services, collaborate cross-functionally, write maintainable code.
Seeking an AWS Data Engineer (Senior) with extensive experience in PySpark and SQL. Must have experience with Amazon EMR or Amazon Glue for data pipelines and data models using Amazon Redshift or Snowflake, Amazon Athena, and Presto. Experience with Airflow for orchestration is required. Bachelor's degree in Computer Science or related field is preferred. Strong problem-solving and communication skills are required.
As a Business Intelligence and Visualization Specialist, you will help clients make sense of complicated data, drive their business forward, and deliver their product lines more efficiently.
All Filters
No Results
No Results
