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Assistant Mlops Jobs (NOW HIRING)

Qualysoft

Fur ein Enterprise-KI-Projekt wird ein erfahrener MLOps Engineer gesucht. Ziel ist der Aufbau und ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

Apple

Machine Learning (MLOps) Engineer

Cupertino, CA · On-site

As an MLOps Engineer, you will be the backbone of our machine learning infrastructure, ensuring ... Comfort using LLM-based tools such as Claude, Gemini, or ChatGPT to assist with code generation ...

Apple

Machine Learning (MLOps) Engineer

Cupertino, CA

$216K - $324K/yr

As an MLOps Engineer, you will be the backbone of our machine learning infrastructure, ensuring ... Leverage AI coding assistants and LLM-based tools (e.g., Claude, Gemini, GitHub Copilot) to ...

PathAI

Associate Director, MLOps Engineering

Boston, NY · On-site +1

Use of AI assistants (e.g. CoPilot, Cursor, Claude) across platform development lifecycle. It Would ... Expertise in MLOps principles, including model lifecycle management, feature stores, model ...

Eliassen Group

MLOps / DevOps Engineer

Charlotte, NC · On-site +1

$70 - $81/hr

Support and improve MLOps platforms with a focus on reliability, scalability, and automation ... These tools assist our hiring teams in different ways, including but not limited to, assistance in ...

Eliassen Group

MLOps / DevOps Engineer

Charlotte, NC · On-site

$70 - $81/hr

Support and improve MLOps platforms with a focus on reliability, scalability, and automation ... These tools assist our hiring teams in different ways, including but not limited to, assistance in ...

Eliassen Group

MLOps / DevOps Engineer

Charlotte, NC · On-site

$70 - $81/hr

Support and improve MLOps platforms with a focus on reliability, scalability, and automation ... These tools assist our hiring teams in different ways, including but not limited to, assistance in ...

Copart, Inc.

DevOps Engineering Intern

Dallas, TX · On-site

AI / MLOps Support * Assist with deployment and monitoring of machine learning and AI applications. * Support AI workflows including model deployment and inference services. * Collaborate with Data ...

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Assistant Mlops information

What are Assistant MLOps?

Assistant MLOps are professionals who support the deployment, monitoring, and management of machine learning models in production environments. They assist senior MLOps engineers with tasks like automating workflows, managing data pipelines, maintaining infrastructure, and ensuring model performance. Their role bridges the gap between data science and IT operations, helping organizations scale and maintain their AI solutions efficiently. Assistant MLOps often have knowledge of cloud services, CI/CD tools, and basic programming, and they work closely with data scientists and engineers.

What is the difference between Assistant Mlops vs Data Engineer?

AspectAssistant MlopsData Engineer
Required CredentialsCertifications in cloud platforms, basic scripting, ML toolsComputer science degree, SQL, Python, data architecture
Work EnvironmentCollaborates with ML teams, supports deployment pipelinesBuilds data pipelines, manages databases, processes large datasets
Industry UsageAI/ML projects, cloud-based environmentsData infrastructure, analytics, big data solutions

Assistant Mlops and Data Engineer roles share overlapping skills in cloud platforms and scripting. However, Assistant Mlops focuses on supporting ML deployment and operations, while Data Engineers primarily build and maintain data infrastructure. Both roles are essential in data-driven organizations but serve different functions within the data ecosystem.

What are some typical daily responsibilities for an Assistant MLOps professional?

As an Assistant MLOps professional, you can expect your daily tasks to involve supporting the deployment, monitoring, and maintenance of machine learning models in production environments. This often includes collaborating with data scientists to automate model training and testing workflows, managing cloud-based resources, and ensuring that data pipelines are running smoothly. You'll also help troubleshoot issues related to model performance or infrastructure and assist in implementing best practices for version control and continuous integration. Working closely with both engineering and data teams, you'll play a key role in ensuring that ML models remain reliable and scalable in real-world applications.

What are the key skills and qualifications needed to thrive as an Assistant MLOps, and why are they important?

To thrive as an Assistant MLOps, you need a solid understanding of machine learning fundamentals, programming (especially Python), and experience with cloud platforms; a degree in computer science or a related field is typically preferred. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, and version control systems (e.g., Git) is important, and certifications in cloud services (AWS, Azure, GCP) can be advantageous. Strong problem-solving, communication, and collaboration skills help you bridge the gap between data science and operations teams. These combined skills ensure efficient deployment, monitoring, and maintenance of machine learning models in production environments.
More about Assistant Mlops jobs
What cities are hiring for Assistant Mlops jobs? Cities with the most Assistant Mlops job openings:
What are the most commonly searched types of Mlops jobs? The most popular types of Mlops jobs are:
What states have the most Assistant Mlops jobs? States with the most job openings for Assistant Mlops jobs include:
What job categories do people searching Assistant Mlops jobs look for? The top searched job categories for Assistant Mlops jobs are:
Assistant Mlops jobs near you
Infographic showing various Assistant Mlops job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 75% Full Time, 21% Part Time, 1% Temporary, and 2% Contract. Highlights an 99% Physical, and 1% Remote job distribution.

MLOps Engineer

Qualysoft

Remote

Contractor

Re-posted 21 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
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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