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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Engineer - **Company:** siemens energy - **Location:** Barcelona, Spain - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Artificial Intelligence, Amazon Web Services, Microsoft Azure, C Sharp (Programming Language), Software Quality, Code Review, Continuous Integration, Data Integration, Extract Transform Load (ETL), Github, Monitoring of Systems, Python (Programming Language), Microsoft Office, NumPy, Ansible, Tensorflow, Scala (Programming Language), Google Cloud, Pytorch, Pandas, Containerization, AI Platforms, Gitlab-ci, Scikit Learn, Kubernetes, Infrastructure Automation Frameworks, Information Technology, Machine Learning Operations, Terraform, Docker - **Published:** August 6, 2026 - **Apply:** https://www.buscojobs.com.es/software-engineer-en-barcelona-ID-365671128 ## About the Role What You Bring A Master's degree in Computer Science or a related field. Over five years of experience as a software engineer, with at least three years focused on ML/AI and MLOps. Strong proficiency in Python and experience with languages such as C#, Java, Scala, or Go. In-depth knowledge of ML frameworks like TensorFlow, PyTorch, scikit-learn, and data libraries such as Pandas and NumPy. Hands-on experience with MLOps tools including Kubeflow, MLflow, TensorFlow Extended (TFX), and CI/CD platforms like Azure DevOps, GitLab CI or GitHub Actions. Proficiency with cloud platforms (AWS, Azure, GCP), containerization tools (Docker), orchestration systems (Kubernetes), and Infrastructure as Code tools like Terraform or Ansible. ## Description Software Engineer (MLOps, AI) About the Role Location Spain Barcelona Barcelona Country: PORTUGAL Remote vs. Office Hybrid (Remote/Office) Company Siemens Energy Organization EVP Global Functions Business Unit Digital Products and Solutions Full / Part time Full-time Experience Level Experienced Professional A Snapshot of Your Day As a Software Engineer within the Scalable Core team, you will collaborate with a diverse group of talented professionals to design, develop, and deploy cutting-edge ML/AI platforms that drive Siemens Energy's intelligent energy management solutions.Your day might include working with Python code for machine learning pipelines, integrating MLOps tools like Kubeflow or MLflow, and ensuring seamless deployment across cloud, on-premises, and edge environments.You'll engage in collaborative problem-solving sessions, participate in code reviews, and contribute to enhancing our developer experience by implementing automated quality assurance processes.Additionally, you'll stay updated with the latest advancements in AI/ML to continuously innovate and improve our platform offerings.How You'll Make an Impact Design, build, and maintain scalable ML/AI platforms that enable the creation and deployment of intelligent energy management solutions.Create and optimize MLOps pipelines for efficient model training, experimentation, and lifecycle management.Integrate tools for automatic hyperparameter tuning and ensure AI model Service Level Agreements (SLAs) are met to maintain high performance and reliability.Work closely with data engineers, software developers, and other stakeholders to manage ETL processes and ensure seamless data integration within ML pipelines.Utilize containerization and orchestration technologies like Docker and Kubernetes to deploy solutions across cloud, on-premises, and edge environments.Contribute to the development of CI/CD pipelines, monitoring systems, and automated quality assurance processes to enhance overall developer productivity and software quality.What You Bring A Master's degree in Computer Science or a related field.Over five years of experience as a software engineer, with at least three years focused on ML/AI and MLOps.Strong proficiency in Python and experience with languages such as C#, Java, Scala, or Go.In-depth knowledge of ML frameworks like TensorFlow, PyTorch, scikit-learn, and data libraries such as Pandas and NumPy.Hands-on experience with MLOps tools including Kubeflow, MLflow, TensorFlow Extended (TFX), and CI/CD platforms like Azure DevOps, GitLab CI or GitHub Actions.Proficiency with cloud platforms (AWS, Azure, GCP), containerization tools (Docker), orchestration systems (Kubernetes), and Infrastructure as Code tools like Terraform or Ansible. ## Related Videos - [Vectorize all the things! 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