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Build and maintain backend systems and integrations that automate critical healthcare workflows using Python/TypeScript and event-driven architectures.
Lead GenAI and voice/audio ML infrastructure at a healthcare SaaS company, designing scalable platforms so product teams can ship AI-powered features like Call Intelligence and AI Receptionist.
Build and maintain scalable data pipelines, vector stores, and LLM-driven BI systems using Python, Spark, and cloud ML services to power real-time AI applications.
Build and scale a production-grade ML platform for 300+ data scientists using Databricks MLOps and AWS SageMaker, automating CI/CD, monitoring, and multi-tenant infrastructure with Python and Terraform.
Build and maintain ETL/ELT pipelines in Python and SQL on AWS, optimizing cloud data lakes/lakehouses for performance and cost while collaborating with AI teams to productionize ML prototypes.
Designs and maintains data pipelines, builds analytics solutions, and integrates ML models using Python and SQL for an AI-driven media platform.
Build and optimize cloud data pipelines, real-time processing, and Lakehouse architectures using Python, PySpark, and SQL to feed AI models and business analytics.
Build and own the Snowflake/dbt pipeline that powers Sovos’s US revenue data chain, transforming billing and deferred revenue into close-ready financial outputs for FP&A and leadership.
Senior Data Engineer builds and maintains a Snowflake/dbt pipeline that turns billing and revenue data into close-ready financial outputs for FP&A and leadership, ensuring reliability and documentation quality for both finance and AI consumers.
Build and maintain cloud data pipelines, ETL/ELT workflows, and ML model services using Python, SQL, AWS, Airflow, and dbt to power analytics and AI features for a logistics company.
Design and maintain a Snowflake-based financial data pipeline for a global tax-compliance SaaS, using dbt to transform billing, revenue, and close data for finance teams and AI consumers.
Build and industrialize AI/ML pipelines for Crédit Agricole, turning experiments into secure, scalable production systems using MLOps, LLMOps, and data engineering.
Build and deploy AI solutions (LLMs, RAG, ML) to optimize Safran Aircraft Engines’ customer support and service operations, translating business needs into robust, explainable models.
Build and deploy cutting-edge AI solutions for clients, focusing on RAG, chatbots, NLP, and LLM/VLM models while collaborating on internal projects and client engagements.
Build and own the MLOps and data infrastructure for a neurotechnology startup, designing pipelines to ingest, version, and serve neural data for scalable model training and deployment.
Designs and maintains cloud-native data and AI pipelines, implements MLOps/LLMOps, and ensures observability and cost optimization for robust data platforms.
Build and maintain scalable data pipelines and GenAI platforms on AWS using Spark, Iceberg, and Bedrock to power analytics, AI, and RAG systems.
Lead a small team of senior data engineers to build and maintain scalable data infrastructure (Spark, Kafka, Airflow) and enable AI/ML workflows for a global fashion resale platform.
Build and maintain an Analytics Factory for large clients, designing data pipelines, optimizing flows, and transforming raw data into dashboards using SQL, PowerBI, Scala, Spark, and Lakehouse architectures.
Build and maintain AI-ready data pipelines and platforms to accelerate drug discovery and development in a hybrid R&D team.
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