AI Job Radar

MLOps Jobs – Seite 26

Aktuelle KI-Jobs mit MLOps, passende Lernpfade und Bewerbungsbezug.

Wie du MLOps für Bewerbungen nutzt

Wenn ein Job MLOps verlangt, sollte der Skill nicht nur als Stichwort im CV stehen. Besser sind ein kurzer Projektbeleg, ein Kursnachweis oder ein Portfolio-Beispiel. Für den Bewerbungscheck wird geprüft, ob der Skill in deinem Lebenslauf wirklich belegbar ist.

655
Treffer
121
Unternehmen
93.8
Durchschn. Score
171
Remote

10 Treffer auf dieser Seite. Insgesamt 655 Treffer. Weitere Treffer sind über die Seitennavigation, Firmen-, Skill- und Jobdetailseiten erreichbar.

US-SeattleUSAgreenhouse2026-08-28

Warum echter KI-Job: The role explicitly focuses on building, training, deploying and researching ML models for fraud detection. The description highlights a core focus on ML throughout the entire lifecycle.

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase th…

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USAstatic_url2026-08-27

Warum echter KI-Job: The job title and company (ServiceNow AI) clearly indicate a core focus on machine learning. The description explicitly mentions 'Machine Learning Engineer' and 'Agentic Systems', suggesting deep involvement in the development and deployment of ML models.

Senior Staff Machine Learning Engineer, Agentic Systems - Moveworks

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New York CityUSAFullTimeashby2026-08-27

Warum echter KI-Job: The role explicitly focuses on deploying and advising on OpenAI's generative AI products for government and non-profit organizations. It requires deep technical expertise in the API, prototyping, and translating complex concepts – all core AI activities.

About the Team The AI Deployment Engineering team is responsible for ensuring the safe and effective deployment of Generative AI applications for developers and startups. We act as a trusted advisor and thought partner for our customers, working to build an effective backlog of GenAI use cases for…

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USUSAgreenhouse2026-08-25

Warum echter KI-Job: The role explicitly focuses on designing, building, training, deploying and owning ML models for a core business function (Capital Underwriting). The description details the use of advanced ML techniques and frameworks. It's an end-to-end ML team.

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase th…

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CA - San FranciscoUSAgreenhouse2026-08-25

Warum echter KI-Job: The role explicitly focuses on building and deploying AI workflows within the Finance organization, with a strong emphasis on LLMs, agentic systems, and telemetry. The description details core responsibilities centered around AI development and implementation.

Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first techn…

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New York, NYSwedenlever2026-08-25

Warum echter KI-Job: The role explicitly focuses on building and evolving machine learning models for personalized experiences, including recommendation systems and large language models. The description highlights a strong emphasis on taking models from research to production at…

The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Blend to Discover Weekly, we’re behind some of Spotify’s most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you’ll keep…

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AI Engineer - Database Engineering

Snowflake · US-CA-Menlo Park

95/100
US-CA-Menlo ParkGermanyFullTimeashby2026-08-25

Warum echter KI-Job: The role explicitly focuses on building and deploying AI features within the core database engine, including agentic workflows, context engineering, evaluation pipelines, and optimization. The requirements clearly state 5+ years of experience shipping AI feat…

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collabor…

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Toronto, ON, CanadaGermanygreenhouse2026-08-25

Warum echter KI-Job: The role is explicitly focused on building and maintaining generative AI systems for recipe content creation and a supporting MLOps platform. The job description heavily emphasizes AI/ML technologies and their application to core business functions.

We are hiring a Machine Learning Engineer in our ML Solutions squad to help build innovative generative AI products that provide AI-powered assistants to HelloFresh's culinary Chefs helping them editorialize content, validate recipe data, detect issues, suggest corrections, and ideate. As a Machine…

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US-CA-Menlo ParkUSAFullTimeashby2026-08-25

Warum echter KI-Job: The role explicitly focuses on building AI-powered features within Snowflake's core database engine, including agentic workflows, context engineering, and evaluation pipelines. The requirements and 'nice to have' sections heavily emphasize AI/ML experience an…

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collabor…

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Senior Machine Learning Operations Engineer

Mercury · Any Office or Remote

95/100
Any Office or RemoteUSAgreenhouse2026-08-24

Warum echter KI-Job: The role is entirely focused on building and operating the production ML lifecycle, including model deployment, observability, and retraining. It directly involves working with models developed by Data Scientists and ensuring their reliable operation in a pro…

Mercury's use of machine learning in risk decisioning is growing fast in scope and in stakes. Models increasingly drive real-time decisions about fraud and financial crime, and the Machine Learning Platform (MLP) team exists to build a paved path from a trained model to a reliable production deploy…

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