AI/ML Engineer

Quick Facts

• Role: AI/ML Engineer

Description

You will design, train, and evaluate machine learning models and build LLM-based solutions, including prompt engineering. The role focuses on developing data pipelines, deploying models to production using MLOps, and monitoring model quality. You will work with Data Science, Backend, and Product teams to implement RAG and vector database capabilities and to define model success metrics.

Responsibilities

• Design, train, and evaluate machine learning models
• Develop LLM-based solutions and apply prompt engineering techniques
• Build and maintain data processing and preparation pipelines
• Deploy models to production environments and monitor model quality
• Implement and optimize RAG and vector database solutions
• Collaborate on feature engineering and model development with Data Science
• Containerize and orchestrate ML services (Docker, Kubernetes)
• Deploy models on cloud platforms (AWS SageMaker, GCP Vertex AI, Azure ML)
• Automate training and deployment workflows (MLflow, Kubeflow, Airflow)
• Partner with Product to define requirements and success metrics
• Ensure code quality, technical documentation, and software engineering best practices

Requirements

• Minimum 3 years of commercial experience in designing and deploying ML models
• Very good Python knowledge and experience with PyTorch and/or TensorFlow
• Experience with language models (LLMs) and frameworks such as LangChain or LlamaIndex
• Knowledge of MLOps and deployment tools (MLflow, Kubeflow, Airflow)
• SQL knowledge and work experience with large datasets
• Experience with Docker and Kubernetes
• Knowledge of at least one cloud platform (AWS, GCP, or Azure)

Benefits

• Career development and participation in AI R&D projects
• Flexible benefits platform (sports card, private medical care, shopping vouchers, event tickets)
• Access to an e-learning platform and training/conference budget
• Access to modern GPU computing infrastructure
• Employee referral program