Top Tech Jobs & Startup Jobs in Seattle, WA

Staff-level platform engineer to improve and scale inherited Scala systems, redesign data layers for ML/AI, build a Rust service framework, enhance observability and resilience, shape developer tooling and standards, and work across JVM, Rust, Python, SQL, and Spark.

The Sr. Product Manager will oversee the transformation of pharmacy payment integrity through AI automation, design workflows, and collaborate with teams to enhance customer-facing analytics and operational processes.

The Senior Technical Data Product Manager will oversee the data product roadmap, collaborating with data engineering and architecture teams. Responsibilities include assessing legacy systems, developing product roadmaps, driving cross-functional deliveries, and ensuring technical requirements are met, aiming for swift execution and measurable impact.

Own end-to-end client data migrations: reverse-engineer legacy ETL, design and build Airflow DAGs and Spark jobs, validate and reconcile data at scale, document architecture and decisions, and coordinate cross-functional teams through go-live and hypercare.

Lead and grow the AI/ML Engineering team, manage core AI/ML platform development, ensure production-grade service operational excellence, and develop product strategies.

The Data Scientist will build machine learning models to enhance claim audits, optimize performance, and improve healthcare decision-making by analyzing complex data sets.

The Sr/Staff Frontend Engineer will develop new web applications, enhance UI experiences, architect solutions, and collaborate with various stakeholders to ensure a scalable and secure platform.

The NLP Scientist will solve complex medical document understanding problems using NLP and CV methodologies, optimize models for performance, and make data-driven decisions.

The Staff Data Scientist will advance machine learning models to optimize claim audits and improve business outcomes in healthcare.

The Staff Data Scientist will lead the development and deployment of ML and GenAI systems to detect billing errors and fraud in healthcare payments, collaborating with cross-functional teams.