Machine Learning Engineer - AI Solutions

Key Responsibilities :

• Design, build, and optimize machine learning models for classification, regression, NLP, computer vision, recommendation systems, or generative AI use cases.
• Perform data preprocessing, feature engineering, and model selection to deliver high-quality outcomes. Implement end-to-end machine learning pipelines from data ingestion to model deployment.
• Develop NLP models for text classification, NER, embeddings, document understanding, and chatbot / agentic workflows.
• Work with modern AI frameworks for LLM fine-tuning, prompt engineering, RAG, and generative AI solutions.
• Deploy ML models in production environments using CI / CD and MLOps platforms.
• Monitor model performance, drift, and accuracy; implement retraining or optimization as required.
• Work with Docker, Kubernetes, Airflow, MLflow, or cloud-native ML services.
• Work with data engineers to improve data pipelines, data quality, and real-time data processing.
• Manage structured and unstructured data sources across cloud ecosystems.
• Stay updated with the latest advancements in machine learning, deep learning, and generative AI.
• Evaluate new models, algorithms, and techniques; contribute to experimentation and POCs.
• Collaborate with product managers, software engineers, and domain experts to deliver AI-driven features.
• Translate business problems into ML / AI solutions with measurable impact.

Required Skills & Qualifications :

Preferred Skills : (Nice to Have)

(ref : hirist.tech)