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Builds and maintains AWS-based data pipelines and Spark jobs in a Data Mesh architecture using Python and Agile workflows.
Build and maintain AI/ML pipelines, deploy models, and manage lifecycle with tools like MLflow, Kubeflow, or cloud platforms (AWS SageMaker/Azure ML).
Senior Software Engineer building and optimizing web applications for language-learning products using Ruby/Rails, JS, Vue, and AWS.
Build and own Duetto’s Python/PySpark data lakehouse that powers real-time hotel pricing decisions, migrating from batch to streaming pipelines on AWS while driving data quality and AI-assisted tooling.
Build and maintain Contentful’s internal AI platform, integrating generative AI, ML models, and APIs with TypeScript/Node.js to enable teams to ship AI-powered features efficiently.
Build a full-stack veterinary platform with React/React Native frontends, Node.js/Python backends, and AWS cloud infrastructure, integrating AI diagnostics and analytics.
Build and optimize AWS-based data pipelines and ML workflows using SageMaker, Kinesis, Glue, and Redshift, ensuring low-latency real-time and batch processing with Python and AWS services.
Designs and builds scalable AWS data pipelines using Python, PySpark, Airflow, and streaming tech to process high-volume data for analytics and warehousing.
Build and maintain scalable data pipelines and ML models to power Kogan.com’s eCommerce operations, enabling data-driven decisions across marketing, logistics, and finance.
Builds and maintains data pipelines, deploys ML models, and improves forecasting for a renewable-energy company.
Build and deploy ML models to forecast commodity flows and detect anomalies using geospatial and maritime data, working end-to-end from prototyping to production on AWS.
Build and deploy AI/ML models (forecasting, CV, NLP) in cloud/air-gapped environments, collaborating with engineers to drive operational efficiency and present insights to stakeholders.
Build, train, and deploy AI/ML models (e.g., time-series, CV, NLP) to solve business problems, then monitor and iterate them in production with MLOps tooling.
Design and deploy ML, GenAI, and predictive models using Python, LLMs, RAG, and cloud AI platforms to drive business growth and customer experiences.
Designs and builds AI/ML models and agentic systems to automate workflows, enhance client engagement, and drive decision-making across retail, marketing, and operations using Python, LLMs, and cloud platforms.
Builds and deploys ML models, GenAI apps, and predictive systems using Python, LLMs, RAG, and cloud AI platforms to drive business growth and customer experience.
Design and implement scalable cloud data architectures, lead Data Lakehouse development, and build ETL/ELT pipelines using Python, SQL, and Spark for a government-linked AI platform.
Design and deliver AI-ready data platforms, ML pipelines, and GenAI-specific data flows for clients using cloud ecosystems like AWS, Azure, and GCP.
Design and build scalable cloud-native data pipelines and lakehouse architectures for a government housing agency, using Python, Spark, Kafka, and AWS services.
Builds and scales the backend services for a high-performance generative AI platform, optimizing compute, storage, and networking for enterprise-grade ML workloads.
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