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Build and optimize scalable data pipelines on Databricks using Spark, Delta Lake, and Unity Catalog to power analytics and ML workflows for enterprise clients.
Build and maintain data pipelines, clean and provision data, and develop ML algorithms using Python, SQL, Spark, and Kafka to extract business insights.
Build and maintain scalable data pipelines and ML algorithms using Python, Spark, Kafka, and SQL to deliver business insights and drive digital transformation.
Build and run the AIOps platform that keeps AI models, LLM pipelines, and agents reliable, scalable, and cost-efficient in AWS/Azure.
Build and improve Veeva Link’s data pipelines and cloud-based data platform using Java/Python, Spark, and cloud services to power life-sciences expert matching and clinical-trial outreach.
Contract DevOps Engineer builds and maintains AWS-based CI/CD pipelines, Kubernetes clusters, and observability for a global SaaS platform using ArgoCD, GitHub Actions, and Splunk.
Build and run the cloud platform that powers the company’s AI services on AWS and Kubernetes, automating deployments with Terraform and CI/CD while supporting MLOps workflows like SageMaker, MLflow, Airflow and Kubeflow.
Build and deploy AI-driven data analytics and generative AI solutions on Azure and GCP, including MLOps pipelines and agentic AI workflows.
Build and maintain high-scale back-end systems for a global travel booking platform using Scala/Kotlin, Kafka, Spark, and modern CI/CD pipelines.
Build and deploy ML models and MLOps pipelines using Python, TensorFlow/PyTorch, and cloud platforms like Azure Databricks for real-time, event-driven data solutions across industries.
Build and maintain ML models for an energy-data platform that collects sensor and consumption data from buildings to help owners cut costs and emissions.
Build open-source AI/ML and data analytics platforms using Python and Kubernetes, leveraging tools like Kubeflow and MLFlow for public cloud and private infrastructure.
Build and maintain data pipelines in Python, C# and .NET that turn sensor, alarm and activity data into reliable datasets for AI-powered care products like Sensio Insight.
Build and fine-tune large language models for Avito’s products, optimizing training pipelines and inference speed for production-scale NLP systems.
Build and maintain ETL/ELT pipelines, data architectures, and ML pipelines using Azure Databricks, Python, SQL, and Kafka to drive energy-sector insights and automation.
Act as a technical advisor during pre-sales, designing AI/LLM and modern data platform solutions for enterprises, and guiding clients from discovery to implementation.
Build and deploy ML models and data pipelines using Python, Spark, and Airflow, integrating classic ML with LLMs for anomaly detection in production systems.
Build and deploy ML models and AI systems for enterprise clients, focusing on LLMs, NLP, and computer vision to solve industrial, automotive, and software-engineering challenges.
Build and deploy AI/ML models for industrial use cases like predictive maintenance and process optimization, using Python, TensorFlow/PyTorch, and MLOps pipelines.
Build and maintain ML pipelines using Airflow, MLflow, and GCP; migrate on-premise systems to cloud-native environments and ensure scalable, reliable data workflows.
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