Erwartungsmanagement Anforderungen Mehrjahrige Erfahrung als MLOps Engineer, ML Engineer oder Data ... Engineer Sehr gute Kenntnisse in Kubernetes-/OpenShift-basierten Umgebungen Erfahrung mit ML ...
Erwartungsmanagement Anforderungen Mehrjahrige Erfahrung als MLOps Engineer, ML Engineer oder Data ... Engineer Sehr gute Kenntnisse in Kubernetes-/OpenShift-basierten Umgebungen Erfahrung mit ML ...
Data Engineer
Milwaukee, WI · On-site
$112K - $135K/yr
The Data Engineer is responsible for the comprehensive data and reporting infrastructure at ... Experience with MLOps pipelines (DVC, Airflow, etc.) Experience with API data integrations ...
Data Engineer
Milwaukee, WI · On-site
$112K - $135K/yr
The Data Engineer is responsible for the comprehensive data and reporting infrastructure at ... Experience with MLOps pipelines (DVC, Airflow, etc.) Experience with API data integrations ...
WI · On-site
$140 - $190/hr
Partner closely with data scientists and AI researchers to translate experimental models into ... in MLOps, DevOps, Data Engineering, Machine Learning, or Software Engineering ; * Degree in ...
WI · On-site
$140 - $190/hr
Partner closely with data scientists and AI researchers to translate experimental models into ... in MLOps, DevOps, Data Engineering, Machine Learning, or Software Engineering ; * Degree in ...
Senior MLOps Engineer (Remote)
Menomonee Falls, WI · On-site
$104K - $144K/yr
Collaborate with Data Scientists and Engineers across the full ML lifecycle, including building and scaling ETL pipelines, deploying models into customer-facing applications, and enabling efficient ...
Senior MLOps Engineer (Remote)
Menomonee Falls, WI · On-site
$104K - $144K/yr
Collaborate with Data Scientists and Engineers across the full ML lifecycle, including building and scaling ETL pipelines, deploying models into customer-facing applications, and enabling efficient ...
Der Fokus liegt auf Big-Data-Engineering , ML/LLM-Workloads , MLOps-Automatisierung sowie der nahtlosen Integration in das Microsoft-Okosystem. 520 - 560 a day Rahmenbedingungen Start: Marz/April ...
Der Fokus liegt auf Big-Data-Engineering , ML/LLM-Workloads , MLOps-Automatisierung sowie der nahtlosen Integration in das Microsoft-Okosystem. 520 - 560 a day Rahmenbedingungen Start: Marz/April ...
ML Ops Engineer
Hales Corners, WI · On-site
Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
New
ML Ops Engineer
Hales Corners, WI · On-site
Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
New
ML Ops Engineer
Wauwatosa, WI · On-site
Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
New
ML Ops Engineer
Wauwatosa, WI · On-site
Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
New
ML Ops Engineer
Franklin, WI · On-site
Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
New
ML Ops Engineer
Franklin, WI · On-site
Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
New
ML Ops Engineer
Butler, WI · On-site
Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
New
ML Ops Engineer
Butler, WI · On-site
Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
New
ML Ops Engineer
Pewaukee, WI · On-site
Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
New
ML Ops Engineer
Pewaukee, WI · On-site
Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
New
ML Ops Engineer
Lannon, WI · On-site
Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
New
ML Ops Engineer
Lannon, WI · On-site
Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
New
ML Ops Engineer
New Berlin, WI · On-site
Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
New
ML Ops Engineer
New Berlin, WI · On-site
Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
New
ML Ops Engineer
Brown Deer, WI · On-site
Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
New
ML Ops Engineer
Brown Deer, WI · On-site
Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
New
ML Ops Engineer
Waukesha, WI · On-site
Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
New
ML Ops Engineer
Waukesha, WI · On-site
Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
New
ML Ops Engineer
Nashotah, WI · On-site
Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
New
ML Ops Engineer
Nashotah, WI · On-site
Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
New
ML Ops Engineer
Thiensville, WI · On-site
Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
New
ML Ops Engineer
Thiensville, WI · On-site
Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
New
ML Ops Engineer
North Lake, WI · On-site
Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
New
ML Ops Engineer
North Lake, WI · On-site
Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
New
ML Ops Engineer
Milwaukee, WI · On-site
Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
New
ML Ops Engineer
Milwaukee, WI · On-site
Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
New
ML Ops Engineer
Sussex, WI · On-site
Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
New
ML Ops Engineer
Sussex, WI · On-site
Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
New
ML Ops Engineer
West Milwaukee, WI · On-site
Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
New
ML Ops Engineer
West Milwaukee, WI · On-site
Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining ... Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot ...
New
Mlops Data Engineer information
What is an MLOps data engineer?
MLOps Data Engineers are professionals who blend expertise in machine learning (ML), operations (Ops), and data engineering to streamline the deployment and management of ML models in production environments. They design and maintain data pipelines, automate workflows, and ensure the scalability, reliability, and reproducibility of machine learning systems. Their role bridges the gap between data scientists and IT operations, enabling seamless integration of ML models into real-world applications.
What are the key skills and qualifications needed to thrive as an MLOps data engineer?
To thrive as an MLOps Data Engineer, you need a strong background in data engineering, machine learning workflows, and software development, usually supported by a degree in computer science or a related field. Expertise with cloud platforms (such as AWS, GCP, or Azure), CI/CD pipelines, containerization tools (like Docker and Kubernetes), and familiarity with orchestration frameworks are typically required, along with certifications in cloud or data engineering. Strong problem-solving abilities, collaboration, and clear communication set professionals apart in this role. These skills and qualities are critical to efficiently deploying scalable machine learning solutions and ensuring smooth collaboration between data science and engineering teams.
What are some common challenges MLOps data engineers face when deploying machine learning models into production?
MLOps Data Engineers often encounter challenges such as ensuring seamless integration between data pipelines and model serving infrastructure, managing consistent data quality, and automating model retraining and monitoring. Another common hurdle is maintaining scalability and reliability as data volumes grow, and efficiently collaborating with data scientists, software engineers, and DevOps teams. Addressing these challenges requires strong communication skills, familiarity with cloud platforms, and a proactive approach to troubleshooting and automation.
What is the difference between Mlops Data Engineer vs Data Scientist?
| Aspect | Mlops Data Engineer | Data Scientist |
|---|---|---|
| Required Skills | Machine learning deployment, cloud platforms, scripting, data pipelines | Statistical analysis, programming, data visualization, machine learning modeling |
| Certifications | Cloud certifications, ML engineering courses | Data science certifications, statistical courses |
| Work Environment | Data pipelines, cloud infrastructure, ML deployment systems | Data analysis, modeling, research environments |
| Industry Usage | Tech companies, AI-focused firms, cloud service providers | Research institutions, analytics firms, tech companies |
The main difference between an Mlops Data Engineer and a Data Scientist lies in their focus areas. Mlops Data Engineers specialize in deploying, maintaining, and scaling machine learning models within production environments, emphasizing infrastructure and automation. Data Scientists primarily focus on analyzing data, building models, and deriving insights. Both roles require strong technical skills, but their day-to-day tasks and career paths differ significantly.
Are MLOps Data Engineers in demand?
MLOps Data Engineers are in high demand due to the increasing adoption of machine learning and AI across industries. They are skilled in deploying, managing, and maintaining ML models using tools like Docker, Kubernetes, and cloud platforms, making their expertise highly sought after in data-driven organizations.
Is MLOps required for data engineers?
MLOps is increasingly important for data engineers involved in deploying and maintaining machine learning models, as it encompasses practices like automation, monitoring, and version control. While not always mandatory, knowledge of MLOps tools such as Docker, Kubernetes, and CI/CD pipelines enhances a data engineer's ability to support scalable and reliable ML systems.
What are popular job titles related to Mlops Data Engineer jobs in Wisconsin?
For Mlops Data Engineer jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Mlops Data Engineer jobs in Wisconsin look for?
The top searched job categories for Mlops Data Engineer jobs in Wisconsin are:
What cities in Wisconsin are hiring for Mlops Data Engineer jobs?
Cities in Wisconsin with the most Mlops Data Engineer job openings:
Contractor
Re-posted 26 days ago
Job description
Fur ein Enterprise-KI-Projekt wird ein erfahrener MLOps Engineer gesucht. Ziel ist der Aufbau und Betrieb regelkonformer, skalierbarer End-to-End Machine-Learning-Workflows von der Entwicklung bis zum produktiven Einsatz.
Rahmenbedingungen
Start: ASAP
Laufzeit: Ende 2026, Verlangerung moglich
Auslastung: 100 %
Arbeitsmodell: Remote bevorzugt, gelegentliche Vor-Ort-Termine nach Absprache
400 - 450 a day
Aufgaben
Aufbau und Betrieb von End-to-End Data-Science- und ML-Workflows
Implementierung von ML-Orchestrierungslosungen (z. B. Kubeflow Pipelines)
Integration von ML-Tracking- und Experiment-Tools (MLflow, TensorBoard, o. A.)
Automatisierung von Training-, Deployment- und Monitoring-Prozessen
Entwicklung und Pflege von Python-basierten ML-Applikationen
Umsetzung von CI/CD- und GitOps-Prinzipien fur ML-Pipelines
Sicherstellung von Security & Schwachstellenmanagement fur Code, Container und Modelle
Betrieb und Weiterentwicklung produktiver KI-Anwendungen
Einbindung regulatorischer Rahmenbedingungen (z. B. AI Act, interne Policies, Kundenvorgaben)
Abstimmung mit Plattform-, Fach- und Projektteams inkl. Erwartungsmanagement
Anforderungen
Mehrjahrige Erfahrung als MLOps Engineer, ML Engineer oder Data Engineer
Sehr gute Kenntnisse in Kubernetes-/OpenShift-basierten Umgebungen
Erfahrung mit ML-Orchestrierung, ML-Tracking und Monitoring
Sehr gute Python-Kenntnisse
Sehr gute Deutsch und Englischkenntnisse
Interessiert?
Bitte senden Sie uns Ihren aktuellen Lebenslauf inklusive Ihrer Verfugbarkeit sowie Ihrer Stundensatzvorstellung. Wir freuen uns auf Ihre Ruckmeldung.
Sie konnen mich gerne uber Freelancermap per E-Mail unter elena.kahraman@qualysoft.com oder uber LinkedIn kontaktieren.
Vielen Dank fur Ihr Verstandnis! +43 699 14402417
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