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35 Treffer für Senior ML Engineer Jobs
Noch nichts dabei? Es gibt 27 weitere Jobs, die zu deiner Suche passen könnten
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Schnelle Bewerbung
We are looking for a Staff ML/AI Data Engineer to lead this transformation by building scalable infrastructure (data volume per source is growing by hundreds of MB per hour), robust data pipelines, and efficient MLOps workflows. In this high-impact, new role, you will partner with product, data engineers, data scientists and data analysts to enable real-time, predictive insights and drive data-driven innovation. * Develop scalable data infrastructure: Lead the design and implementation of real-time data pipelines and ML/AI solutions to advance data maturity across the organization. * Infrastructure & tooling: Experience developing scalable infrastructures for data analytics, ML and AI.
We are looking for a Staff ML/AI Data Engineer to lead this transformation by building scalable infrastructure (data volume per source is growing by hundreds of MB per hour), robust data pipelines, and efficient MLOps workflows. In this high-impact, new role, you will partner with product, data engineers, data scientists and data analysts to enable real-time, predictive insights and drive data-driven innovation. * Develop scalable data infrastructure: Lead the design and implementation of real-time data pipelines and ML/AI solutions to advance data maturity across the organization. * Infrastructure & tooling: Experience developing scalable infrastructures for data analytics, ML and AI.
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Erfahrung in mindestens einem state-of-the-art ML-, NLP- oder CV-Framework wie z. B. scikit-learn, HF Transformers, PyTorch, TensorFlow, Chainer, SpaCy, YOLO * Sehr gute Programmierkenntnisse, insbesondere mit Fokus auf ML, Datenaufbereitung und Integration in real-world-applications (Must-have: Python; Von Vorteil: SQL, Java, C#, R; Erfahrung mit Containertechnologien (z. B. Docker, Kubernetes) oder Cloud-basierten ML-Produkten z. B. AWS SageMaker, Azure ML)
Erfahrung in mindestens einem state-of-the-art ML-, NLP- oder CV-Framework wie z. B. scikit-learn, HF Transformers, PyTorch, TensorFlow, Chainer, SpaCy, YOLO * Sehr gute Programmierkenntnisse, insbesondere mit Fokus auf ML, Datenaufbereitung und Integration in real-world-applications (Must-have: Python; Von Vorteil: SQL, Java, C#, R; Erfahrung mit Containertechnologien (z. B. Docker, Kubernetes) oder Cloud-basierten ML-Produkten z. B. AWS SageMaker, Azure ML)
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You collaborate cross-functionally with Data Scientists, Engineers, Product Managers, and business stakeholders to translate requirements into technical solutions. * You identify and evaluate GenAI/ML use cases to improve internal services and client-facing products. * You build and maintain robust GenAI/ML systems, including cloud infrastructure and appropriate monitoring. * You build, train and deploy ML models that focus on benchmarking, recommendations and forecasting of carbon footprint and emissions data. * You stay on top of the latest advancements in AI and advocate Data Science and ML fundamentals in the Digital department. * You have at least 3 years of experience in a Machine Learning role (as a Data Scientist, Software Engineer, Machine Learning /AI
You collaborate cross-functionally with Data Scientists, Engineers, Product Managers, and business stakeholders to translate requirements into technical solutions. * You identify and evaluate GenAI/ML use cases to improve internal services and client-facing products. * You build and maintain robust GenAI/ML systems, including cloud infrastructure and appropriate monitoring. * You build, train and deploy ML models that focus on benchmarking, recommendations and forecasting of carbon footprint and emissions data. * You stay on top of the latest advancements in AI and advocate Data Science and ML fundamentals in the Digital department. * You have at least 3 years of experience in a Machine Learning role (as a Data Scientist, Software Engineer, Machine Learning /AI
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Recruit, develop, and retain top CV/ML scientists, data engineers, and platform architects. This executive will oversee the strategy and build-out of advanced computer vision (CV) and machine learning (ML) solutions that power real-time sports data collection, athlete tracking, video analysis, and fan engagement products. This leader will be accountable for technical excellence, innovation velocity, and building a world-class engineering culture around data, models, and applied ML. * Build AI/ML platforms that optimize latency, model accuracy, and computational efficiency under live sports conditions. * 15+ years of leadership experience in AI/ML, with at least 7+ years leading CV-centric platforms at scale. * Proven experience scaling cloud-native architectures on AW
Recruit, develop, and retain top CV/ML scientists, data engineers, and platform architects. This executive will oversee the strategy and build-out of advanced computer vision (CV) and machine learning (ML) solutions that power real-time sports data collection, athlete tracking, video analysis, and fan engagement products. This leader will be accountable for technical excellence, innovation velocity, and building a world-class engineering culture around data, models, and applied ML. * Build AI/ML platforms that optimize latency, model accuracy, and computational efficiency under live sports conditions. * 15+ years of leadership experience in AI/ML, with at least 7+ years leading CV-centric platforms at scale. * Proven experience scaling cloud-native architectures on AW
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Mehr als 3 Jahre Erfahrung als Machine Learning Engineer, Data Engineer oder in einer ähnlichen Funktion mit starkem ML-Hintergrund * Entwerfen, Erstellen und Pflege der ML CI/CD-Pipeline und Workflows, die die Datenerfassung, Datenanalyse, Experimente, Modellschulung, Modellbereitstellung und Überwachung in der Produktion automatisieren * Automatisierung von Modellschulungs- und Freigabe-Workflows und Aufbau von Diensten rund um ML-Inferenz und Modellbereitstellung für die Laufzeitverarbeitung * Implementierung von Maßnahmen zur Verbesserung der Zuverlässigkeit und Leistung der ML-Infrastruktur * Aktive Suche nach Möglichkeiten zur Verbesserung der ML-Pipeline-Entwicklung und des Betriebsprozesses * Erfahrung in der Erstellung, Bereitstellung und War
Mehr als 3 Jahre Erfahrung als Machine Learning Engineer, Data Engineer oder in einer ähnlichen Funktion mit starkem ML-Hintergrund * Entwerfen, Erstellen und Pflege der ML CI/CD-Pipeline und Workflows, die die Datenerfassung, Datenanalyse, Experimente, Modellschulung, Modellbereitstellung und Überwachung in der Produktion automatisieren * Automatisierung von Modellschulungs- und Freigabe-Workflows und Aufbau von Diensten rund um ML-Inferenz und Modellbereitstellung für die Laufzeitverarbeitung * Implementierung von Maßnahmen zur Verbesserung der Zuverlässigkeit und Leistung der ML-Infrastruktur * Aktive Suche nach Möglichkeiten zur Verbesserung der ML-Pipeline-Entwicklung und des Betriebsprozesses * Erfahrung in der Erstellung, Bereitstellung und War
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Praktikant:in als Machine Learning Engineer (m/w/d) bei der U-Glow GmbH
Praktikant:in als Machine Learning Engineer (m/w/d) bei der U-Glow GmbH
U-Glow GmbH
Mülheim
Teilweise Home-Office
Du entwickelst ML-Pipelines und Modelle in Python und arbeitest mit modernen KI-Frameworks.
Du entwickelst ML-Pipelines und Modelle in Python und arbeitest mit modernen KI-Frameworks.
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Your missionAs an MLOps Engineer, you will play a critical role in ensuring our machine learning models transition seamlessly from research to production. - Experience in ML Experimentation and registry platforms such as W&B or MLFLow. - Familiar with ML/NN frameworks. - Strong ability to collaborate with cross-functional teams, including data scientists, engineers, and clients.
Your missionAs an MLOps Engineer, you will play a critical role in ensuring our machine learning models transition seamlessly from research to production. - Experience in ML Experimentation and registry platforms such as W&B or MLFLow. - Familiar with ML/NN frameworks. - Strong ability to collaborate with cross-functional teams, including data scientists, engineers, and clients.
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Schnelle Bewerbung
The Role: As AI Architect / Machine Learning Engineer, you will drive the development and deployment of sophisticated AI systems that are revolutionizing healthcare diagnostics. * Experience with Cloud AI/ML services (AWS, GCP, Azure) and Big Data technologies.
The Role: As AI Architect / Machine Learning Engineer, you will drive the development and deployment of sophisticated AI systems that are revolutionizing healthcare diagnostics. * Experience with Cloud AI/ML services (AWS, GCP, Azure) and Big Data technologies.
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Junior Machine Learning Engineer (m/w/d) · AMAI GmbH
Junior Machine Learning Engineer (m/w/d) · AMAI GmbH
AMAI GmbH
Karlsruhe, Deutschland
Teilweise Home-Office
Du unterstützt unser Team von erfahrenen Machine Learning Engineers bei der Entwicklung und Implementierung von KI-Lösungen.
Du unterstützt unser Team von erfahrenen Machine Learning Engineers bei der Entwicklung und Implementierung von KI-Lösungen.
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We're looking for an ML / DevOps Engineer to own the infrastructure powering our AI systems — ensuring that data pipelines, training clusters and deployed run fast, reliably and at scale. * Build and operate the infrastructure behind our ML pipelines and video data processing tools * Design and maintain CI/CD for ML — automating builds, testing and releases - You make advanced AI systems run like clockwork — turning complex ML research into dependable, production-grade infrastructure. * 5–7 years experience running large-scale ML or data systems in production * Pragmatic, reliable and comfortable balancing ML experimentation with engineering rigor
We're looking for an ML / DevOps Engineer to own the infrastructure powering our AI systems — ensuring that data pipelines, training clusters and deployed run fast, reliably and at scale. * Build and operate the infrastructure behind our ML pipelines and video data processing tools * Design and maintain CI/CD for ML — automating builds, testing and releases - You make advanced AI systems run like clockwork — turning complex ML research into dependable, production-grade infrastructure. * 5–7 years experience running large-scale ML or data systems in production * Pragmatic, reliable and comfortable balancing ML experimentation with engineering rigor
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