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 ...
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 ...
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 ...
... in data and analytics engineering focus on leveraging advanced technologies and techniques to ... MLOps frameworks, managing daily operations across global delivery teams while engaging health ...
... in data and analytics engineering focus on leveraging advanced technologies and techniques to ... MLOps frameworks, managing daily operations across global delivery teams while engaging health ...
The Director, Applied AI & ML Engineering will lead the strategy, architecture, and deployment of ... Implement best practices in MLOps, data management, and continuous delivery pipelines. * Deliver ...
Quick apply
The Director, Applied AI & ML Engineering will lead the strategy, architecture, and deployment of ... Implement best practices in MLOps, data management, and continuous delivery pipelines. * Deliver ...
Senior Forward Deployed Engineer, Microsoft AI&Data
$104K - $141K/yr
Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt ... Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science ...
Senior Forward Deployed Engineer, Microsoft AI&Data
$104K - $141K/yr
Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt ... Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science ...
Principal Data Architect
Milwaukee, WI · 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 ...
Principal Data Architect
Milwaukee, WI · 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 ...
Senior ML Ops Engineer
Middleton, WI · On-site
$123K - $170K/yr
... data, digital infrastructure, and AI-powered innovation ... What You Will Do: · Design, build, and maintain scalable MLOps solutions that support the end-to ...
Quick apply
Senior ML Ops Engineer
Middleton, WI · On-site
$123K - $170K/yr
... data, digital infrastructure, and AI-powered innovation ... What You Will Do: · Design, build, and maintain scalable MLOps solutions that support the end-to ...
AI Engineer
Middleton, WI · On-site
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.
AI Engineer
Middleton, WI · On-site
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.
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.
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.
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.
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.
Lead ML Ops Engineer
Milwaukee, WI · 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
Milwaukee, WI · 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
Milwaukee, WI · On-site
$101K - $133K/yr
Experience in MLOps, DevOps, or related fields, with a focus on enterprise-level solutions ... Degree in computer science, data science, or related field preferred. Technical Competencies
Lead ML Ops Engineer
Milwaukee, WI · On-site
$101K - $133K/yr
Experience in MLOps, DevOps, or related fields, with a focus on enterprise-level solutions ... Degree in computer science, data science, or related field preferred. Technical Competencies
Lead ML Ops Engineer
Racine, WI · 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
Lead ML Ops Engineer
Racine, WI · 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
Principal Data Scientist
Appleton, WI · On-site
Data engineering and feature engineering concepts at scale, including pipelines built on modern ... Designing and deploying models into production with the surrounding MLOps practices-CI/CD ...
Principal Data Scientist
Appleton, WI · On-site
Data engineering and feature engineering concepts at scale, including pipelines built on modern ... Designing and deploying models into production with the surrounding MLOps practices-CI/CD ...
... code, MLOps, and cloud data engineering. Here's what your day-to-day will look like: * Manage the entire content development lifecycle and deadlines. * Source and recruit top-tier subject-matter ...
... code, MLOps, and cloud data engineering. Here's what your day-to-day will look like: * Manage the entire content development lifecycle and deadlines. * Source and recruit top-tier subject-matter ...
... code, MLOps, and cloud data engineering. Here's what your day-to-day will look like: * Manage the entire content development lifecycle and deadlines. * Source and recruit top-tier subject-matter ...
... code, MLOps, and cloud data engineering. Here's what your day-to-day will look like: * Manage the entire content development lifecycle and deadlines. * Source and recruit top-tier subject-matter ...
... code, MLOps, and cloud data engineering. Here's what your day-to-day will look like: * Manage the entire content development lifecycle and deadlines. * Source and recruit top-tier subject-matter ...
... code, MLOps, and cloud data engineering. Here's what your day-to-day will look like: * Manage the entire content development lifecycle and deadlines. * Source and recruit top-tier subject-matter ...
Mlops Data Engineer information
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 engineers in demand?
MLOps Data Engineers are in high demand due to the increasing adoption of machine learning and AI across industries. They are needed to develop, deploy, and maintain scalable ML systems, often requiring skills in cloud platforms, automation, and tools like Docker and Kubernetes. The role offers strong job growth prospects as organizations prioritize operationalizing AI solutions.
What are the key skills and qualifications needed to thrive as an MLOps Data Engineer, and why are they important?
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 are MLOps Data Engineers?
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 data engineer in MLOps?
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 skills in cloud platforms, automation, and machine learning tools tend to earn higher salaries.
What engineer makes 500,000 a year?
Highly experienced senior MLOps Data Engineers with specialized skills in cloud platforms, automation, and large-scale data processing can earn salaries approaching or exceeding $500,000 annually, especially in competitive tech hubs or large organizations. Such roles often require advanced certifications, extensive experience, and expertise in tools like Kubernetes, Docker, and cloud services like AWS or Azure.
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
Posted 2 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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