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Mlops Data Engineer 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 ...

Data Engineer

Milwaukee, WI ยท 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 ...

Senior MLOps Engineer (Remote)

Menomonee Falls, WI ยท 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 ...

Senior Forward Deployed Engineer- AWS

Milwaukee, WI ยท On-site

$103K - $141K/yr

Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation * Experience with MLOps/LLMOps ...

Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation * Experience with MLOps/LLMOps ...

This role is ideal for an engineer who combines solid software, data, and ML engineering skills ... MLOps practices (CI/CD, Docker, model serving). * Familiarity with data science libraries and ...

This role is ideal for an engineer who combines solid software, data, and ML engineering skills ... MLOps practices (CI/CD, Docker, model serving). * Familiarity with data science libraries and ...

Principal Data Architect

Milwaukee, WI ยท Hybrid

$160K - $190K/yr

You will work closely with engineering, analytics, and platform teams to design scalable data ... Exposure to AI/ML data pipelines or MLOps frameworks * Financial services or investment domain ...

WI ยท On-site

$130 - $160/hr

Collaborate with data engineering teams to ensure high-quality, governed, and accessible data for ... Experience with MLOps, vector databases, orchestration frameworks, and AI observability platforms.

New

WI ยท On-site

$120 - $180/hr

... data, digital infrastructure, and AI-powered innovation. What You Will Do ... Design, build, and maintain scalable MLOps solutions that support the end-to-end machine learning ...

New

WI ยท On-site

$140 - $190/hr

... data, digital infrastructure, and AI-powered innovation. What You Will Do ... Design, build, and maintain scalable MLOps solutions that support the end-to-end machine learning ...

New

Senior ML Ops Engineer

Middleton, WI ยท On-site

$123K - $170K/yr

... data, digital infrastructure, and AI-powered innovation ... What You Will Do: ยท Design, build, and maintain scalable MLOps solutions that support the end-to ...

WI ยท On-site

$147.20 - $210.30/hr

Summary Gainwell Technologies is seeking a highly skilled AI Engineer to design, develop, and ... Familiar with cloud platforms (AWS, Azure, GCP), MLOps practices, and big data tools (Spark, Hadoop ...

New

Lead ML Ops Engineer

Milwaukee, WI ยท On-site

$101K - $133K/yr

Align AI and MLOps initiatives with business objectives, ensuring platforms and pipelines meet ... Degree in computer science, data science, or related field preferred. Technical Competencies

Lead ML Ops Engineer

Racine, WI ยท On-site

$96K - $126K/yr

Align AI and MLOps initiatives with business objectives, ensuring platforms and pipelines meet ... Degree in computer science, data science, or related field preferred. Technical Competencies

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Mlops Data Engineer information

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

AspectMlops Data EngineerData Scientist
Required SkillsMachine learning deployment, cloud platforms, scripting, data pipelinesStatistical analysis, programming, data visualization, machine learning modeling
CertificationsCloud certifications, ML engineering coursesData science certifications, statistical courses
Work EnvironmentData pipelines, cloud infrastructure, ML deployment systemsData analysis, modeling, research environments
Industry UsageTech companies, AI-focused firms, cloud service providersResearch 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 machine learning models using tools like Docker, Kubernetes, and cloud platforms, making their expertise highly sought after in data-driven organizations.

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 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 is the salary of MLOps Data Engineer?

The salary of an MLOps Data Engineer typically ranges from $90,000 to $150,000 annually, depending on experience, location, and company size. Professionals with advanced skills in cloud platforms, automation, and machine learning tools may earn higher compensation.
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 cities in Wisconsin are hiring for Mlops Data Engineer jobs? Cities in Wisconsin with the most Mlops Data Engineer job openings:

Contractor

Re-posted 12 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?
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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
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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