Senior Machine Learning Engineer

• Solution Development: Design, develop, and implement end-to-end machine learning pipelines for various use cases to improve our internal Siemens processes.
• Technical Leadership: Provide expertise in ML engineering best practices, including data preprocessing, model training, evaluation, deployment, and incorporating MLOps and LLMOps approaches for scalable and maintainable solutions.
• Project Ownership and Management: Lead projects from conception to deployment, translating business requirements into scalable technical solutions, ensuring timely delivery and alignment with business objectives.
• Collaboration: Work closely with an international team of diverse backgrounds, including engineers, product managers, and other stakeholders, to integrate AI solutions into existing systems.
• Communication: Clearly articulate complex technical concepts to non-technical stakeholders and team members. Comfort with proactively raising concerns, suggesting alternatives, and engaging in constructive debate when appropriate
• Mentorship: Mentor junior team members and contribute to the overall skill development within the team.

You’re excited to build on your existing expertise, including:

• Education: Advanced degree in Computer Science, Data Science, Machine Learning, Mathematics, Statistics, Physics, or a related field.
• Preferred 7+ Years of Experience in machine learning engineering or data science roles.
• Demonstrated ability to manage and deliver complex projects.
• Strong Proficiency in programming languages such as Python.
• Experience with machine learning frameworks (e.g., TensorFlow, PyTorch).
• Experience with cloud-native ML development (Azure, AWS).
• Familiarity with large language models and natural language processing as well as experience with LLM frameworks (langchain, promptflow)
• Proven ability to deliver end-to-end projects (i.e. from exploration to endpoint serving)
• Knowledge of big data technologies (Snowflake, Spark).
• Experience with data visualization tools and libraries.
  • Knowledge of software development best practices, including version control (e.g., GitLab) and collaborative coding.