Full Stack and Machine Learning Engineer

ackend teams to integrate new forecasting and regression models into the existing architecture

• Design, develop, and maintain the machine learning engine, focusing on optimizing model performance and accuracy
• Work closely with data scientists to refine and implement new machine learning algorithms for forecasting and regression tasks
• Troubleshoot and resolve complex issues related to model deployment, prediction, or inference
• Perform regular monitoring and maintenance tasks to ensure the ML engine is running efficiently and effectively

Model Deployment and Hosting:

• Design, develop, and deploy a scalable model hosting platform e.g. using Kubeflow, Kserve etc
• Configure and handle the platform for seamless model serving and inference
• Ensure models are accurately versioned, tracked, and deployed with minimal downtime

Required Machine Learning and AI Expertise:

• Currently working on machine learning projects and staying up-to-date with the latest trends and techniques
• Proven understanding of machine learning fundamentals, including supervised and unsupervised learning, deep learning, and natural language processing
• Experience with Generative AI (GenAI) technologies, such as text-to-image models or conversational AI is a plus
• Familiarity with explainability techniques and model interpretability methods

Technical Skills:

• Programming languages: Java, Python, or other relevant programming languages
• Machine Learning Libraries: StatsModel, Scikit-learn, TensorFlow, PyTorch etc
• Data Preprocessing: pandas, NumPy, scikit-learn etc
• Model Deployment: Docker, Kubernetes (MLflow/Kubeflow is plus)
• Cloud Computing Platforms: AWS, Azure, or private cloud platforms
• Experience with Java Spring Boot for building scalable web applications
• Angular experience for crafting intuitive and user-friendly interfaces

Preferred Knowledge/Skills

• Previous experience as a Full Stack Developer with expertise in Java Spring Boot and Angular
• Strong understanding of web application architecture and scalability principles
• Excellent problem-solving skills and ability to work independently with R&D mindset
• Strong communication and collaboration skills, with experience working in agile teams

Good to Have:

• Experience with DevOps practices (e.g., Continuous Integration, Continuous Deployment) for machine learning models
• Certification in machine learning or data science
• Experience with cloud-based machine learning platforms (e.g., AWS SageMaker, Azure Machine Learning)
• GenAI exposure

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A collection of over 377,000 minds building the future, one day at a time in over 200 countries. We're dedicated to equality, and we encourage applications that reflect the diversity of the communities we work in. All employment decisions at Siemens are based on qualifications, merit, and business need. Bring your curiosity and creativity and help us shape tomorrow!
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