Top Remote Senior Level Data Engineer Jobs in Seattle, WA

Join Block as a Senior Machine Learning Platform Engineer in the ML Foundations team. Build self-service tooling for the model lifecycle, work with internal customers, and design scalable systems for ML use cases.

Design, develop, and maintain scalable solutions for metrics, reports, and analyses. Translate business problems into analysis requirements and collaborate with the team to measure customer experience. Develop queries, visualizations, and troubleshoot data-quality issues. Review and recommend improvements for backend data sources.

The Staff Machine Learning Engineer at Cruise will drive the robotics aspects of the Simulation Smart Agents software stack, collaborating with specialists to deploy algorithms and ML models, optimize ML pipelines, create data pipelines, define metrics for evaluation, and accelerate engineer velocity within Simulation. The role requires expertise in robotics, machine learning, ML frameworks, runtime optimization, and programming skills in C++ or Python.

The Head of Data at Square will lead centralized Data functions including Data Science, Analytics, Machine Learning, and Data Engineering teams. Responsibilities include driving data strategy, overseeing data functions, establishing data governance, and delivering insights to drive business performance.

Seeking a Senior Data Engineer to create and own a data engineering roadmap, collaborate with product and engineering teams, and build data processing pipelines and infrastructure. Must have 5+ years of core data engineering experience with technical proficiency in SQL, Python, Snowflake, dbt, Airflow, Kubernetes, Docker, DataDog, and AWS.

Design, build, and manage distributed services and pipelines for Underwriting & Credit at Cash App. Lead multi-person projects, ensure high code quality, collaborate with various teams, and contribute to the growth of development capabilities. Remote work with a distributed team in the USA and Canada.

As a Machine Learning Engineer, you will analyze opportunities, propose ideas, train and evaluate ML models, run experiments, and deploy solutions to production. You will contribute to ML architecture and be part of the ML community at Stripe. Responsibilities include improving performance, evaluating systems, and ensuring model quality. Minimum requirements include 5 years of end-to-end ML development experience, an advanced degree in a quantitative field, and proficiency in Python, Scala, and Spark.