Mlops - 19+ pracovních nabídek

Are you… Interested in working for a company that is dedicated to sustainability? Interested in developing your career in a leading packaging and printing industry? Interested in working for a company that is dedicated to sustainability? If so, read on! *Esko,** a **Veralto company**, is a global pr

About The Team A big data team responsible for building and running applications and AI applications processing large volumes of data is searching for a new intern colleague. If you are interested in real time data processing, MLOPs, not afraid of polyglot stack (we love Java/Kotlin/Python and more)

You might be the perfect match if you are/have: At least 5 years of professional experience in DevOps, MLOps, or a similar role; Hands-on experience in building and deploying machine learning systems (excluding hosted LLM APIs), using frameworks such as PyTorch, TensorFlow, or JAX; Experience design

Requirements: Bachelor's or Master's degree in Mathematics, Computer Science, Machine Learning, or related field Mastery over Data Science frameworks (pandas, pyspark, sklearn and shap) and MLOPS frameworks (MLFlow, Kedro/Airflow, Hyperopt/Optuna and Great Expectations) in Python Experience with bui

Strong experience as a Senior Data Engineer with solid MLOps background. Hands-on expertise with Azure Databricks (Workflows, Delta Lake, Unity Catalog). Proficiency in PySpark , SQL Warehouses, and production-grade pipeline development. Experience with CI/CD (GitHub Actions or Azure DevOps). Famili

Y ou might be the perfect match if you are/have: At least 5 years of professional experience in Platform Engineering, DevOps, or similar roles; Hands-on, production experience with Kubernetes (EKS/GKE/AKS), including upgrades, autoscaling, networking, RBAC, and reliability; Practical experience buil

Requirements and Skills: Strong proficiency in Python: development of production-grade code, knowledge of libraries for ML and automation. Experience in MLOps (2+ years): hands-on experience in deploying and managing ML models in industrial/operational use. ML Expertise: understanding of the model l

5+ years of experience in ML Engineering with production systems Strong architecture design and documentation skills Expert-level Python Experience with AWS (SageMaker preferred) Hands-on experience with MLflow and GitLab CI/CD Experience with TensorFlow or PyTorch Proven experience building scalabl

Wymagania – Must have Minimum 3 lata doświadczenia w obszarze DevOps / MLOps / Software Engineering, w tym praca z modelami ML na produkcji. Bardzo dobra znajomość Docker i Kubernetes (zarządzanie klastrami, Helm, Ingress). Doświadczenie z chmurą publiczną – preferowany Azure (Azure ML, AKS, ACR) lu

Strong Python skills (Pandas, Scikit-learn, TensorFlow or similar). Experience in building and maintaining data pipelines. Hands-on experience with ML Ops practices: CI/CD, monitoring, versioning. Experience with AWS and cloud-based ML solutions. Solid background in data analysis and data visualizat

Strong Python skills (Pandas, Scikit-learn, TensorFlow or similar). Experience in building and maintaining data pipelines. Hands-on experience with ML Ops practices: CI/CD, monitoring, versioning. Experience with AWS and cloud-based ML solutions. Solid background in data analysis and data visualizat

WHO YOU ARE: Master's or PhD degree in Computer Science, Data Science, Software Engineering, or a related technical field, Proficiency in programming languages commonly used in data science such as Python or R, with experience in libraries like pandas, NumPy, scikit-learn, and data visualization too

Requirements: Bachelor's or Master's degree in Mathematics, Computer Science, Machine Learning, or related field Mastery over Data Science frameworks (pandas, pyspark, sklearn and shap) and MLOPS frameworks (MLFlow, Kedro/Airflow, Hyperopt/Optuna and Great Expectations) in Python Experience with bui

Requirements and Skills: Strong proficiency in Python: development of production-grade code, knowledge of libraries for ML and automation. Experience in MLOps (2+ years): hands-on experience in deploying and managing ML models in industrial/operational use. ML Expertise: understanding of the model l

Wcześniejsze doświadczenia w tworzeniu i wdrażaniu aplikacji w Pythonie. Bardzo dobra znajomość systemów Linux (Debian, RHEL). Swobodne poruszanie się w obszarze tworzenia aplikacji konteneryzowanych uruchamianych w Kubernetes. Doświadczenie w pracy z rozwiązaniami chmurowymi (preferowana GCP). Umie

Requirements: Experience: Senior-level experience in MLOps or Production ML. Tech Stack: Strong Python , ML Frameworks ( PyTorch/TensorFlow ), and MLOps tools ( MLflow, Kubeflow, or SageMaker ). IaC: Experience with Terraform and Cloud optimization. Defense Readiness: EU Citizenship is mandatory. La

You come from either an Engineering or Data Science background, with production grade experience in an enterprise setting, with either experience or interest in Machine Learning and Data Science. You therefore tick the following points: Key Requirements: A degree in engineering, computer science, ma

5+ years of experience in ML Engineering with production systems Strong architecture design and documentation skills Expert-level Python Experience with AWS (SageMaker preferred) Hands-on experience with MLflow and GitLab CI/CD Experience with TensorFlow or PyTorch Proven experience building scalabl

Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. 5+ years of experience in machine learning engineering with proven ownership of production ML systems. Strong experience designing and documenting complex ML and data architectures.