Top Data Engineer Jobs in Seattle, WA
Design, implement, and scale critical machine learning components and services to support Snap's most strategic initiatives. Develop a next-generation training framework and AutoML platform. Provide technical direction that influences the entire company.
Principal Machine Learning Engineer responsible for driving the technical roadmap of the Ad Ranking team, designing and implementing critical machine learning models to support Snap's monetization strategies, collaborating with cross-functional teams, and providing technical direction to influence the entire ML community.
Snap Inc is seeking a Machine Learning Engineer with 5+ years of experience to create models that drive value for users, advertisers, and the company. Responsibilities include evaluating technical tradeoffs, code reviews, and building scalable products. Strong understanding of machine learning approaches, algorithms, and collaboration skills are required. Bachelor's degree in a technical field or equivalent experience is necessary.
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Seeking a Senior Machine Learning Engineer to develop innovative pricing algorithms tailored to parking scenarios. Responsibilities include research, optimization, and deploying ML models. Requires a PhD or MS in relevant field, 4+ years of industry experience, proficiency in Python and SQL, and expertise in machine learning algorithms.
Lead machine learning and data science initiatives to enhance the shopping experience and advertising solutions for Chewy. Develop models for product selection, ranking, relevance, and auction algorithms. Collaborate with product and engineering teams to deliver innovative solutions at scale.
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Lead a team of Machine Learning Engineers and Data Scientists in building machine learning solutions for fraud prevention in the financial services industry. Partner with ML ops and platform teams to improve research efficiency and model quality. Evaluate and improve model performance using new algorithms and model architectures. Foster feedback loop with risk operations teams for continuous improvement.
As a Cloud Data & Analytics Implementation Senior Associate at PwC, you will assist clients in choosing a platform, defining their data needs, and migrating them to a modern cloud data environment using cloud providers such as AWS, Azure, GCP, Snowflake, Databricks, or Teradata. Responsibilities include aligning client data strategies to business strategy and working on complex business issues from strategy to execution.
GoodRx is looking for a Sr. Data Engineer to collaborate with teams and build data pipelines to guide business decisions. Responsibilities include defining requirements, designing data solutions, leading projects, and developing data processing pipelines using cloud technology. The role requires 8+ years of experience in big data engineering, expertise in technologies like pySpark, SQL, and AWS services, and the ability to analyze large datasets for insights and solutions.
Seeking a Principal Data Scientist with strong engineering skills to drive technical capabilities in ML and AI across multiple teams. Responsibilities include hands-on development work, tech leadership, advocating for best practices, and providing mentorship.
As a Machine Learning Engineer at ZS, you will be responsible for building, orchestrating, and monitoring model pipelines, scaling machine learning algorithms, implementing ML Ops, writing production-ready code, collaborating with client teams, and staying updated on the latest technologies.
Senior/Staff Machine Learning Engineer responsible for designing, building, and productionizing proprietary machine learning models to solve business challenges. Collaborate with product managers and engineers, maintain code quality, stay updated on emerging tech, and share knowledge through tech talks.
Design and build data pipelines for foundational data sets related to Identity, Account, Profile, and Device data. Collaborate with internal and external teams to define technical requirements, implement ETL strategies, and automate data quality checks. Partner with various tech teams and contribute to all phases of the software development process. Work on cloud-based technology to solve scalability, reliability, and performance challenges.
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