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Senior AI/ML Platform Engineer(m/w/x)
Developing and integrating platform components for a skill management system on AWS. 4+ years building data-centric software frameworks required. Complex AWS cloud infrastructure and robust data pipelines.
Requirements
- University degree in Computer Science, Data Science, Statistics, or comparable qualification
- 4+ years of industry experience in building data-centric software frameworks
- Strong foundation in OOP software development
- Proficiency in Linux-based software development
- Experience with container technologies (Docker), version control (GitLab/GitHub), and CI/CD pipelines
- Agile mindset with experience in modern development practices
- Fluency in written and spoken English
- Advanced fluency in modern Python development, including database management and software testing
- Hands-on cloud-native development experience on AWS
- Proficiency in provisioning and managing scalable cloud resources using Infrastructure as Code (IaC) frameworks such as Terraform or AWS CDK
- Proven track record in large-scale data pipeline orchestration
- Experience preparing and manipulating datasets for model evaluation (structured, semi-structured, and unstructured data)
- Practical experience with the latest large language model (LLM) developments, including RAG architectures, prompt management, and advanced context engineering
- Familiarity with data science frameworks (NumPy, pandas, scikit-learn)
- Experience with deep learning frameworks (PyTorch, TensorFlow)
- Knowledge in one or more of: entity extraction/linking, document classification, knowledge graphs, recommendations/matching
- Experience with orchestration and ML platforms such as Prefect, Airflow, Kubeflow, SageMaker
Tasks
- Break down product requirements into actionable engineering tasks
- Explain data constraints to engineering, product, and stakeholder teams
- Integrate AI/ML models into distributed cloud architectures on AWS
- Design and implement scalable infrastructure using AWS services
- Develop and maintain robust data pipelines and orchestration processes
- Enhance automated deployment, logging, and monitoring setups
- Contribute to text analysis and NLP models to extract and structure core business data
Work Experience
- 4 years
Education
- Bachelor's degree
Languages
- English – Business Fluent
Tools & Technologies
- Docker
- GitLab
- GitHub
- CI/CD
- AWS
- Terraform
- AWS CDK
- NumPy
- pandas
- scikit-learn
- PyTorch
- TensorFlow
- Prefect
- Airflow
- Kubeflow
- SageMaker
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Senior AI/ML Platform Engineer(m/w/x)
Developing and integrating platform components for a skill management system on AWS. 4+ years building data-centric software frameworks required. Complex AWS cloud infrastructure and robust data pipelines.
Requirements
- University degree in Computer Science, Data Science, Statistics, or comparable qualification
- 4+ years of industry experience in building data-centric software frameworks
- Strong foundation in OOP software development
- Proficiency in Linux-based software development
- Experience with container technologies (Docker), version control (GitLab/GitHub), and CI/CD pipelines
- Agile mindset with experience in modern development practices
- Fluency in written and spoken English
- Advanced fluency in modern Python development, including database management and software testing
- Hands-on cloud-native development experience on AWS
- Proficiency in provisioning and managing scalable cloud resources using Infrastructure as Code (IaC) frameworks such as Terraform or AWS CDK
- Proven track record in large-scale data pipeline orchestration
- Experience preparing and manipulating datasets for model evaluation (structured, semi-structured, and unstructured data)
- Practical experience with the latest large language model (LLM) developments, including RAG architectures, prompt management, and advanced context engineering
- Familiarity with data science frameworks (NumPy, pandas, scikit-learn)
- Experience with deep learning frameworks (PyTorch, TensorFlow)
- Knowledge in one or more of: entity extraction/linking, document classification, knowledge graphs, recommendations/matching
- Experience with orchestration and ML platforms such as Prefect, Airflow, Kubeflow, SageMaker
Tasks
- Break down product requirements into actionable engineering tasks
- Explain data constraints to engineering, product, and stakeholder teams
- Integrate AI/ML models into distributed cloud architectures on AWS
- Design and implement scalable infrastructure using AWS services
- Develop and maintain robust data pipelines and orchestration processes
- Enhance automated deployment, logging, and monitoring setups
- Contribute to text analysis and NLP models to extract and structure core business data
Work Experience
- 4 years
Education
- Bachelor's degree
Languages
- English – Business Fluent
Tools & Technologies
- Docker
- GitLab
- GitHub
- CI/CD
- AWS
- Terraform
- AWS CDK
- NumPy
- pandas
- scikit-learn
- PyTorch
- TensorFlow
- Prefect
- Airflow
- Kubeflow
- SageMaker
Like this job?
BetaYour Career Agent finds similar jobs for you every day.
About the Company
Cobrainer GmbH
Industry
IT
Description
Cobrainer ist die führende KI-basierte Skill-Plattform für internes Recruiting, Talent- und Skill-Management.
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