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ML Engineer – Flexible Work, Energy Data Platform
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.
Python & Kubernetes Data Platform Engineer
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.
Data Engineer: Build the data foundation for the future of care
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.
Data Science / ML Engineer
Build and deploy ML models and MLOps pipelines for public-sector clients using Python, TensorFlow/PyTorch, Kafka, and Databricks.
Data Scientist в команду LLM
Build and fine-tune large language models for Avito’s products, optimizing training pipelines and inference speed for production-scale NLP systems.
Senior Data & AI Engineer
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.
Solution Engineer (AI & Big Data) @ Addepto
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.
ML Engineer (Python/Big Data)
Build and deploy ML models and data pipelines using Python, Spark, and Airflow, integrating classic ML with LLMs for anomaly detection in production systems.
Data Scientist / ML Engineer @ Addepto
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.
Poland | Data and MLOps Engineer 1 at Hatch
Build and deploy AI/ML models for industrial use cases like predictive maintenance and process optimization, using Python, TensorFlow/PyTorch, and MLOps pipelines.
MLOps Engineer – Data Analytics Platform
Build and maintain ML pipelines using Airflow, MLflow, and GCP; migrate on-premise systems to cloud-native environments and ensure scalable, reliable data workflows.
Data and MLOps Engineer
Build and maintain scalable data pipelines and MLOps infrastructure for industrial AI solutions in mining, energy, and infrastructure sectors, deploying models in cloud/edge environments.
Data and MLOps Engineer
Build and maintain scalable data pipelines and MLOps workflows for industrial AI solutions in mining, energy, and infrastructure, deploying models in cloud/edge environments.
Senior Data Scientist with Data Engineering Skills (kontraktor)
Senior Data Scientist builds demand-forecasting models for a Polish entertainment network, integrating sales history with external signals and engineering data pipelines in Python and SQL.
Senior Data Scientist with Data Engineering Skills
Build and maintain an end-to-end demand-forecasting system for a nationwide entertainment network, blending sales history with external signals and shipping GLM models in Python/SQL.
Senior Data Engineer - Azure Databricks & Delta Lake
Build and optimize scalable data pipelines on Azure Databricks and Delta Lake, focusing on performance and Python-based workflows with MLflow integration.
Databricks Data Engineer – GenAI & Lakehouse Innovator
Build and maintain scalable data pipelines and Lakehouse architectures using Databricks, PySpark, and Delta Lake to power analytics and GenAI solutions for enterprise clients.
Data Engineer (Insurance Data Platform) | f/m/d
Build and maintain ETL pipelines and data platforms for insurance analytics using AWS Glue, Spark, and Python, ensuring data quality and regulatory compliance.
Senior Data Engineer (M/F/D)
Design and build scalable Lakehouse architectures (Bronze/Silver/Gold) using Databricks and Delta Lake to transform logistics data into BI insights, optimizing ETL/ELT pipelines with PySpark and Azure/AWS/GCP services.
Databricks Data Engineer (ICH Europe)
Build and maintain scalable data pipelines and Lakehouse models on Databricks, using PySpark, Delta Lake, and Medallion architecture to deliver analytics-ready datasets for enterprise clients.