MACHINE LEARNING ENGINEER - Switzerland

Job Title: Machine Learning Engineer – GenAI, Multi-Agent Systems & MLops Specialist 

Job Description

We are seeking a skilled Machine Learning Engineer to build and deploy production-grade AI solutions. These solutions may involve traditional ML models, multi-agent AI systems, or a combination of both. The ideal candidate will have hands-on experience developing GenAI solutions with robust AgentsOps—including testing and validation—and a strong background in MLops. You will collaborate with cross-functional teams and clients to translate complex requirements into scalable, high-quality AI systems.

Responsibilities

• Develop & Deploy: Build and deploy production-level AI solutions, whether as standalone ML models, multi-agent systems, or integrated approaches.
• GenAI & AgentsOps: Design and implement GenAI solutions with comprehensive AgentsOps strategies, ensuring rigorous testing and validation.
• MLops Integration: Develop and maintain MLops pipelines to streamline continuous integration, deployment, and monitoring of AI models.
• Collaboration: Work closely with clients and internal teams to gather requirements and deliver effective solutions.
• Data Engineering: Participate in data preprocessing, feature engineering, and the creation of scalable data pipelines.

Required Qualifications

• Education: Bachelor’s or Master’s degree in a quantitative field (or equivalent practical experience).
• Production Experience: Proven experience in building production-grade GenAI solutions, incorporating proper AgentsOps, testing, and validation practices.
• MLops Expertise: Solid hands-on experience with MLops processes and tools, managing the full lifecycle of AI models in production.
• Technical Skills:
  • Proficiency in Python (or R) and experience with standard ML libraries (e.g., scikit-learn).
  • Familiarity with deep learning frameworks such as PyTorch and TensorFlow/Keras.
  • Exposure to cloud platforms like GCP, AWS, or Azure and distributed processing frameworks (e.g., Apache Spark).
  • Experience with GenAI agents libraries (e.g., LangChain, LangGraph, CrewAI, Autogen, LlamaIndex, etc…) and integrating secure API access to LLM models (e.g., OpenAI’s, Anthropic’s Claude, Hugging Face Inference API, Deepseek API, etc…).
• Problem-Solving: Strong understanding of machine learning algorithms, data pipeline development, and system optimization.

Preferred Skills

• DevOps: Experience with CI/CD practices and container orchestration tools (e.g., Kubernetes).
• Advanced AgentsOps: In-depth knowledge of agent-based system operations.
• Versatility: Proven track record in working with both traditional ML models and multi-agent AI systems.
• Full Stack Development: Familiarity with full stack development is a plus, with an emphasis on backend engineering.

What We Offer

Join a dynamic, innovative team where you’ll work on cutting-edge AI projects and make a significant impact. We provide an environment that supports continuous learning, collaboration, and professional growth. If you’re passionate about leveraging advanced AI techniques to solve real-world challenges, we’d love to hear from you!