AI Job Radar

Model Deployment Jobs – Page 9

Aktuelle KI-Jobs mit Model Deployment, passende Lernpfade und Bewerbungsbezug.

How to use Model Deployment in applications

If a job requires Model Deployment, the skill should be supported by a project, course or portfolio example. The application check reviews whether the skill is actually evidenced in your CV.

89
Results
36
Companies
94.6
Average score
34
Remote

9 results on this page. 89 results in total. More results are available via pagination, company pages, skill pages and job detail pages.

TLM, Machine Learning, Integrity

OpenAI · San Francisco

95/100
San FranciscoUSAFullTimeashby2026-05-26

Why this is a real AI job: Die Rolle ist stark auf Machine Learning und die Entwicklung von Systemen zur Sicherung der Plattformintegrität ausgerichtet. Der Titel erwähnt explizit 'Machine Learning', und die Aufgaben beinhalten Modelltraining, Deployment-Strategien, Schutzmaßnahmen und…

ABOUT THE TEAM The Applied team safely brings OpenAI's technology to the world. Our team launched ChatGPT, Advanced Voice Mode, Deep Research, and many other products, supporting scalable infrastructure and driving safe, responsible deployment. Our customers rely on our APIs to build transformative…

Details Open source / apply

Bengaluru, IndiaUSAgreenhouse2026-05-26

Why this is a real AI job: Die Rolle beinhaltet die Entwicklung und Bereitstellung von ML-basierten Such- und Entdeckungsrelevanzmodellen, die tief in NLP, LLMs und Modellbewertung eingebunden sind. Die Aufgaben sind klar auf KI/ML ausgerichtet und stellen den überwiegenden Kern der Ro…

P-1407 The Applied AI team at Databricks sits at the forefront of advancing AI/ML-powered products. Databricks’ customers are continuously creating new assets (tables, notebooks, dashboards, datarooms, pipelines, sql queries, ml models etc.) on the platform. Some of them can have hundreds of millio…

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Sr Software Engineer, Search

Databricks · Bengaluru, India

95/100
Bengaluru, IndiaUSAgreenhouse2026-05-26

Why this is a real AI job: Die Rolle beinhaltet die Entwicklung und Bereitstellung von ML-basierten Such- und Entdeckungsrelevanzmodellen, die Integration in Databricks-Produkte, sowie die Gestaltung von NLP-Pipelines und Evaluationsrahmen. KI ist der überwiegende Kern der Aufgaben.

P-1407 The Applied AI team at Databricks sits at the forefront of advancing AI/ML-powered products. Databricks’ customers are continuously creating new assets (tables, notebooks, dashboards, datarooms, pipelines, sql queries, ml models etc.) on the platform. Some of them can have hundreds of millio…

Details Open source / apply

Staff Data Scientist

Mercury · Any Office or Remote

90/100
Any Office or RemoteUSAgreenhouse2026-09-10

Why this is a real AI job: The role explicitly focuses on building, validating, deploying, and monitoring machine learning models for fraud detection. The job description heavily emphasizes ML experience and technical skills related to data science and model building. The 'Ideally you…

In 1999 NASA lost contact with its Mars Climate Orbiter after a 9 month journey from Earth. It began its planned orbital insertion maneuver but went out of radio contact after passing behind Mars. While we may never know whether it was destroyed in the atmosphere or re-entered heliocentric space, w…

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Senior Data Scientist

Mercury · Any Office or Remote

90/100
Any Office or RemoteUSAgreenhouse2026-09-10

Why this is a real AI job: The role explicitly focuses on building, validating, and deploying machine learning models for fraud detection and risk mitigation. The job description heavily emphasizes ML techniques and data science principles as core responsibilities.

In 1999, NASA lost contact with its Mars Climate Orbiter after a 9-month journey from Earth. It began its planned orbital insertion maneuver but went out of radio contact after passing behind Mars. While we may never know whether it was destroyed in the atmosphere or re-entered heliocentric space,…

Details Open source / apply

San Francisco, CAUSAgreenhouse2026-08-13

Why this is a real AI job: The role is explicitly focused on building and deploying AI solutions for robotics, working with foundation models, and developing data pipelines for training and deployment. The job description heavily emphasizes ML, data, and AI concepts.

The next frontier for AI is the physical world. At Scale, we're pioneering this shift, moving artificial intelligence from digital spaces into robotics. Our Robotics team builds the critical infrastructure that empowers the most sophisticated robotic efforts. We are currently seeking a strategic ML…

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Staff Machine Learning Engineer

Zscaler · Office - Bangalore, India

90/100
Office - Bangalore, IndiaUSAgreenhouse2026-07-21

Why this is a real AI job: The role explicitly focuses on building and maintaining ML pipelines, solving business problems with ML, and has requirements around ML experience. The company is described as 'AI-forward'.

About Zscaler Zscaler accelerates digital transformation to ensure our customers can be more agile, efficient, resilient, and secure. As an AI-forward enterprise , we are constantly pushing the envelope, leveraging the world’s largest security data lake to power our cloud-native Zero Trust Exchange…

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ParisFranceFull-timelever2026-07-10

Why this is a real AI job: The role explicitly focuses on integrating and deploying Mistral AI's models (LLMs, GenAI) with customer software. The job description highlights collaboration with AI engineers and researchers, and a strong emphasis on technical problem-solving related to AI…

About Mistral At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life. We democratize AI through high-performance, optimized, open-source and cutting-edge models, produ…

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New York, NYSwedenPermanentlever2026-08-31

Why this is a real AI job: The role explicitly focuses on building and maintaining detection models for content moderation, which is a core AI/ML application. The team owns the infrastructure behind these models and their deployment.

We design Spotify’s consumer experience—end to end, moment to moment, across every screen, platform, and partner integration. Our mission is to make listening feel effortless, personal, and joyful for billions of users around the world. That means turning complexity into clarity across hundreds of…

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