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Data Engineer Ml Jobs in Wisconsin (NOW HIRING)

Erwartungsmanagement Anforderungen Mehrjahrige Erfahrung als MLOps Engineer, ML Engineer oder Data ... Engineer Sehr gute Kenntnisse in Kubernetes-/OpenShift-basierten Umgebungen Erfahrung mit ML ...

WI · On-site

$60 - $80/hr

* Build and maintain data pipelines for machine learning models. * Develop Python code to run feature preprocessing and feature engineering on large Datasets. * Monitor the performance of ML models in ...

Data Engineer

Watertown, WI · On-site +1

$109K - $131K/yr

VAS, a URUS Group company, is looking for a Data Engineer to help design, build, and improve the ... Develop and support batch and streaming data architectures for reporting, analytics, and AI/ML ...

Data Engineer

Watertown, WI · On-site

$109K - $131K/yr

VAS, a URUS Group company, is looking for a Data Engineer to help design, build, and improve the ... Develop and support batch and streaming data architectures for reporting, analytics, and AI/ML ...

Data Engineer

Watertown, WI · On-site

$109K - $131K/yr

VAS, a URUS Group company, is looking for a Data Engineer to help design, build, and improve the ... Develop and support batch and streaming data architectures for reporting, analytics, and AI/ML ...

Data Engineer

Watertown, WI · On-site

$109K - $131K/yr

VAS, a URUS Group company, is looking for a Data Engineer to help design, build, and improve the ... Develop and support batch and streaming data architectures for reporting, analytics, and AI/ML ...

Lead Data Engineer

Madison, WI · On-site

$115K - $138K/yr

Experience enabling AI/ML workloads and feature engineering pipelines. * Knowledge of data governance, data quality frameworks, and regulatory compliance requirements.

Data Engineer

Watertown, WI · On-site +1

$109K - $131K/yr

VAS, a URUS Group company, is looking for a Data Engineer to help design, build, and improve the ... Develop and support batch and streaming data architectures for reporting, analytics, and AI/ML ...

Lead Data Engineer

Madison, WI · On-site

$115K - $138K/yr

Experience enabling AI/ML workloads and feature engineering pipelines. * Knowledge of data governance, data quality frameworks, and regulatory compliance requirements. * Experience working within ...

WI · On-site

$100 - $125/hr

Monitor the performance of ML models in production. Required Skills and Qualifications ... Programming languages: SQL, Python * Distributed Computing: Spark * Cloud Infrastructure: AWS

Lead Data Engineer

Grafton, WI · On-site

$112K - $135K/yr

Working under the SVP of Technology and Commercial AI and in close partnership with the AI/ML ... engineering to deliver governed, queryable data products KPIs Data freshness and pipeline ...

Lead Data Engineer

Grafton, WI

$112K - $135K/yr

Working under the SVP of Technology and Commercial AI and in close partnership with the AI/ML ... engineering to deliver governed, queryable data products KPIs Data freshness and pipeline ...

WI · On-site

$125 - $150/hr

The AI Data Engineer is responsible for building and operating high‑quality, governed, and ... Strong hands‑on experience designing and operating data pipelines for analytics, ML, or AI ...

Fur ein langfristig angelegtes Daten- und KI-Programm wird ein Databricks AI / ML Engineer (m/w/d) gesucht. Ziel ist die Entwicklung, Implementierung und der Betrieb skalierbarer Machine-Learning ...

WI · On-site

$100 - $125/hr

Work closely with data scientists, AI engineers and robotics engineers to provide reliable, well-structured data feeds for analytics and ML pipelines. Contribute to technical documentation and ...

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Data Engineer Ml information

What does a data engineer ML do?

A Data Engineer ML (Machine Learning) is responsible for designing, building, and maintaining the data pipelines and infrastructure necessary for machine learning applications. They clean, process, and organize large datasets to ensure data quality and accessibility for data scientists and ML engineers. In addition, they may work on deploying machine learning models to production environments and optimizing data workflows for efficiency and scalability.

What are the key skills and qualifications needed to thrive as a data engineer ML?

To thrive as a Data Engineer ML, you need strong programming skills (especially in Python or Scala), knowledge of data modeling, and a solid foundation in database technologies, typically supported by a degree in computer science or a related field. Familiarity with big data frameworks (like Spark or Hadoop), cloud platforms (AWS, GCP, or Azure), and ETL tools, as well as relevant certifications, is highly beneficial. Excellent problem-solving abilities, teamwork, and clear communication help you collaborate with data scientists and stakeholders effectively. These skills are essential for building robust data pipelines and infrastructure that enable scalable, high-quality machine learning solutions.

How do data engineer ML roles typically collaborate with data scientists and machine learning engineers on projects?

Data Engineer ML professionals work closely with data scientists and machine learning engineers by building and maintaining robust data pipelines, ensuring clean and reliable datasets are readily available for modeling and analysis. They often participate in meetings to understand model requirements, help optimize data storage for performance, and support the deployment of machine learning models into production environments. Effective collaboration involves continuous communication to troubleshoot data issues, implement data validation, and scale solutions as project needs evolve. This teamwork ensures that data-driven projects move efficiently from experimentation to deployment.

What is the difference between Data Engineer Ml vs Data Scientist?

AspectData Engineer MlData Scientist
Required CredentialsBachelor's in CS, Data Engineering certificationsBachelor's/Master's in CS, Data Science certifications
Work EnvironmentBuilding data pipelines, managing databasesAnalyzing data, creating models
Employer & Industry UsageTech companies, finance, healthcareResearch institutions, tech firms, finance

Data Engineer Ml focuses on developing and maintaining data infrastructure and pipelines, while Data Scientists analyze data and build predictive models. Both roles often collaborate but serve different functions within data teams.

What are popular job titles related to Data Engineer Ml jobs in Wisconsin?

For Data Engineer Ml jobs in Wisconsin, the most frequently searched job titles are:

What cities in Wisconsin are hiring for Data Engineer Ml jobs?

Cities in Wisconsin with the most Data Engineer Ml job openings:

Contractor

Re-posted 14 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
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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