Senior Data Engineer, MLOps

🕒 vor 7 Monaten

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Quanata

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201 - 500 Mitarbeiter

🤖 Künstliche Intelligenz

☁️ SaaS

Artificial Intelligence • Insurance • SaaS

Quanata ist ein Unternehmen, das die Versicherer von morgen mit KI-unterstützten Modellierungsfähigkeiten, Echtzeit-Telematiklösungen und innovationsgetriebenen, risikobasierten Akquisitionslösungen stärkt, mit einem Fokus auf kontextbasierten Versicherungslösungen. Sie bieten fortschrittliche kontextuelle und verhaltensbasierte Risikomodellierung, digitale Erlebnisse und telematikbasierte Belohnungsprogramme. Quanata wird von State Farm, einem Branchenführer, unterstützt und nutzt Talent und Technologie aus dem Silicon Valley, um Innovationen im Versicherungssektor voranzutreiben. Ihre Plattform bietet cloud-native Technologielösungen für Versicherer, einschließlich telematikzentrierter, verbraucherorientierter Apps. Mit Sitz in San Francisco, CA, zielt Quanata darauf ab, Schadensprozesse zu modernisieren und die Zeichnungs- und Marketingfähigkeiten für führende Marktversicherer und innovative Insurtechs zu verbessern.

Beschreibung

• Operationalize key data science solutions that enable risk‑prediction products across underwriting, pricing, claims routing, and marketing. • Design and build ML pipelines using industry best practices, primarily leveraging AWS services like SageMaker, and integrating with tools such as MLflow for experiment tracking and data platforms like Snowflake. • Stand‑up and operate a shared feature store (Snowflake Snowpark + Kafka) that supports both batch and real‑time feature retrieval. • Own real‑time inference services, exposing low‑latency endpoints (SageMaker endpoints or EKS micro‑services) and managing blue/green or canary deployments. • Implement comprehensive testing strategies (including Unit, integration, data validation, model validation, and performance testing) within robust CI/CD pipelines to maintain high platform quality. • Enable ML Governance: Manage ML models and data versioning, experiment tracking, and reproducibility. • Implement event‑driven orchestration that triggers automated retraining, evaluation, and redeployment based on data drift or business events. • Monitor production models for performance, drift, and data quality—and drive automated remediation.

🎯 Anforderungen

• Bachelor degree or equivalent relevant experience. • 8 years of industry experience with 2 years focused on MLOps and 2 years in software engineering or equivalent experience. • Comprehensive experience in Python and docker. • Familiarity with build tooling such as bash and bazel. • Advanced proficiency in IaC principles and tools like Terraform. • Demonstrated expertise in designing, deploying, and managing scalable and resilient MLOps solutions on AWS. • Applied expertise in the end-to-end machine learning lifecycle, including data ingestion, preprocessing, model training, deployment, and production monitoring. • Excellent written and verbal communication with a strong collaborative focus. • Proficiency in designing and implementing workflows using tools like AWS Step Functions. • Experience with CI/CD tailored for machine learning systems.

🏖️ Vorteile

• We provide a wide variety of health, wellness and other benefits. • These include medical, dental, vision, life insurance and supplemental income plans for you and your dependents. • A Headspace app subscription. • Monthly wellness allowance. • A 401(k) Plan with a company match. • Given our virtual environment— in order to set you up for success at home, a one-time payment of $2K will be provided to cover the purchase of in-home office equipment and furniture at your discretion. • All employees accrue four weeks of PTO in their first year of employment. • New parents receive twelve weeks of fully paid parental leave which may be taken within one year after the birth and/or adoption of a child. • Each year for professional learning, continuing education and career development, we’re committed to investing in and helping our people grow personally and professionally. • All employees receive up to $5000.