ML Engineer

• Develop, train, and fine-tune Machine Learning models for AI/ML applications
• Design and implement data pipelines for data processing, model training, and inference
• Deploy models using MLOps and integrate them with cloud infrastructure
• Collaborate with product managers and designers to conceptualize AI-driven features
• Research and implement various ML and AI techniques to improve performance
  
   

Required Skills & Qualifications:

 

• Proficiency in Python and ML frameworks such as Scikit-learn, XGBoost, TensorFlow, PyTorch
• Experience with SQL and ETL data pipelines , including data processing and feature engineering
• Experience with Docker and container-based deployments to create cloud-agnostic products
• Strong understanding of AI and Machine Learning concepts such as Supervised Learning, Unsupervised Learning, Deep Learning, and Reinforcement Learning
• Knowledge of at least one cloud platform (AWS, Azure, GCP) and ML deployment strategies (preferably Azure)
• Exposure to LLMs (e.g., OpenAI, Hugging Face, Mistral) and foundation models
• Understanding of various Statistical models