Mid-Level ML Engineer

📋 Description

• Design and deploy ML pipelines from experiments to production with limited supervision
• Build, evaluate, and optimize models across supervised, unsupervised, and generative AI tasks
• Develop and maintain production-grade Python code: modular, tested, and well-documented
• Set up reproducible experimentation environments and pipelines
• Deploy and monitor ML models in production, ensuring stability and performance
• Actively contribute to LLM-based applications, including RAG systems and agent workflows

🎯 Requirements

• Strong grasp of supervised and unsupervised ML: algorithms, evaluation, real-world trade-offs
• Practical experience with classification, regression, and feature engineering in production contexts
• Hands-on experience with deep learning: CNNs, RNNs, Transformers for training and fine-tuning
• Solid understanding of model evaluation, bias-variance, and validation strategies
• Experience with at least one ML domain in depth: NLP, Computer Vision, Recommendation, or Time Series
• Practical experience building LLM-based applications using OpenAI, Anthropic, or Hugging Face APIs