Machine Learning Engineer - Generative AI

About the Role

You are a Machine Learning Engineer with 2-4 years of experience in building and deploying ML-driven solutions, including ML and GenAI-based systems. Your role will involve working across the full ML lifecycle, from data preparation and model development to deployment, monitoring, and continuous improvement in production environments.

Responsibilities

• Build, train, and optimize machine learning and GenAI models for production use cases
• Work with large-scale structured and unstructured datasets (text, images, embeddings, tabular data)
• Implement feature engineering, data preprocessing, and model evaluation pipelines
• Develop and deploy ML/GenAI models
• Integrate ML solutions with backend systems and applications
• Work with embedding models, vector databases, or retrieval-based ML systems where applicable
• Monitor model performance, latency, and quality in production
• Collaborate closely with data engineers, backend engineers, and product teams
• Document model behavior, assumptions, and deployment workflows

You are a Machine Learning Engineer with 2-4 years of experience in building and deploying ML-driven solutions, including ML and GenAI-based systems. Your role will involve working across the full ML lifecycle, from data preparation and model development to deployment, monitoring, and continuous improvement in production environments.

• Build, train, and optimize machine learning and GenAI models for production use cases
• Work with large-scale structured and unstructured datasets (text, images, embeddings, tabular data)
• Implement feature engineering, data preprocessing, and model evaluation pipelines
• Develop and deploy ML/GenAI models
• Integrate ML solutions with backend systems and applications
• Work with embedding models, vector databases, or retrieval-based ML systems where applicable
• Monitor model performance, latency, and quality in production
• Collaborate closely with data engineers, backend engineers, and product teams
• Document model behavior, assumptions, and deployment workflows

Qualifications Required

• 2+ years of hands‑on experience as a Machine Learning Engineer
• Solid understanding of machine learning concepts and algorithms
• Experience with frameworks such as PyTorch, TensorFlow, scikit‑learn, Langchain, LangGraph, etc.
• Familiarity with NLP, embeddings, or deep learning‑based models
• Hands‑on experience with GenAI systems (LLMs, prompt engineering, RAG pipelines, fine‑tuning)
• Experience with data processing using Pandas, NumPy, and SQL
• Understanding of model deployment, inference, and performance optimization
• Experience using Git and working in Linux‑based environments
• Experience with cloud platforms such as AWS / GCP / Azure
• Experience with Docker and containerized deployments
• Strong communication skills with the ability to explain ML/GenAI concepts clearly to both technical and non‑technical stakeholders.