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Senior Data Engineer designing data architectures, executing ETL processes on complex/large datasets, integrating data sources, and collaborating with Data Scientists, primarily using Python/R, Big Data tools, and cloud platforms (AWS/GCP).
Designs and maintains scalable Azure-based data pipelines and platforms for government datasets, enabling AI/ML and analytics. Builds ETL/ELT workflows using tools like ADF, Databricks, Spark, Kafka, and SQL, collaborating with data scientists and MLOps teams.
Design and implement machine learning models using Python and TensorFlow, collaborating with cross-functional teams to integrate ML algorithms into production systems in a fully remote freelance role.
AI Engineer building and deploying machine learning models with PyTorch, TensorFlow, Python, and Scala in Bangalore with remote flexibility.
Senior Software Engineer building AML transaction monitoring and batch data pipelines using Scala, Spark, Kafka, and cloud platforms (Azure/AWS/GCP) to support financial crime prevention at a large bank.
Designs and builds high-throughput cloud data pipelines and low-latency APIs to ingest and serve real-time telemetry data at scale.
Build and optimize Shopee’s e-commerce data warehouse and pipelines, supporting BI, data products, and ML algorithms with big-data tech like Spark and Kafka.
Build and deploy ML models in AWS/Azure for healthcare analytics, refactoring data scientists' code into production batch jobs and optimizing cloud costs.
Lead the design and scaling of high-throughput distributed data pipelines and storage systems for Luma's multimodal foundation models and Physical AI, using Python, Spark/C++/Rust, and PyTorch/Ray.
Data Engineer building and operating high-throughput distributed data pipelines for multimodal foundation models and Physical AI at Luma AI in Singapore, using Python, distributed storage, and GPU environments like PyTorch and Ray.
Design, build, deploy, and optimise AI/ML solutions for global clients as a Forward Deployed AI Engineer at a top-tier consultancy, working with Python, cloud platforms (AWS/Azure/GCP), and MLOps workflows with 50% travel across APAC.
The Data Engineer will design and optimize big data processing pipelines and search applications using Quantexa software, Apache Spark, Scala, and Elasticsearch. The role involves collaborating with cross-functional teams to implement data solutions on the OpenShift Container Platform within a financial compliance context.
Build and maintain scalable BigQuery data pipelines using Cloud Composer and Airflow for AI/ML user experience projects, providing data observability via Monte Carlo and Looker.
Build and maintain scalable data pipelines for AI/ML user experience projects using GCP, Airflow, and Spark, ensuring data quality and reliability.
Software Engineer on Cisco's Webex Engineering Analytics team building and operating Kafka-based streaming applications, Spark/Flink data processing jobs, and scalable distributed big data systems.
Meet the Team Webex Data Analytics Platform (WAP) engineering organization is responsible for developing the big data platform at Webex. The platform forms the base on which other teams, including the WAP team, develop…
This role involves designing, developing, and deploying machine learning models in a cloud environment to support Disney's media and streaming platforms. The engineer will collaborate with cross-functional teams using Agile methodologies to build scalable technical solutions.
Sr. Data Engineer on Slack's Enterprise team at Salesforce, designing and scaling batch and real-time data pipelines, building scalable data models, and contributing to the GovSlack initiative. Core technologies include SQL, Python, Airflow, and data warehouse/OLAP environments.
The ERM Market Risk Analyst II performs market risk analysis, stress testing, sensitivity analysis, and model validation for a Federal Home Loan Bank, using quantitative techniques and the PolyPaths platform to support risk and business decision-making.
Build and optimize high-performance data pipelines and OLAP systems for risk analytics using Java, Spark, and Hive to process petabytes of financial data.
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