AI/ML Engineer
Role Overview
We are looking for a Machine Learning Engineer strongly aligned to model development, experimentation, training, evaluation, and productionization of AI/ML solutions. The ideal candidate should have hands-on experience building ML and deep learning models and working across traditional/legacy models, modern AI models, and frontier/foundation models. Strong Python and MLOps experience is required.
Key Responsibilities
• Design, develop, train, evaluate, and deploy machine learning and deep learning models.
• Own the ML lifecycle from data preparation and feature engineering through model development, evaluation, deployment, and monitoring.
• Select appropriate algorithms and architectures based on business and technical requirements.
• Develop models using Python, TensorFlow, PyTorch, scikit-learn, and related ML frameworks.
• Work with traditional ML models as well as up-to-date deep learning and foundation-model architectures.
• Explore and integrate frontier models, foundation models, and emerging AI models into enterprise AI solutions.
• Work with legacy/traditional AI/ML models where existing business solutions need to be enhanced, migrated, or integrated.
• Perform experimentation, hyperparameter tuning, benchmarking, and performance optimization.
• Build evaluation frameworks for ML, deep learning, and GenAI models.
• Develop production-ready ML pipelines and integrate models into enterprise applications.
• Implement MLOps practices covering model versioning, experiment tracking, CI/CD, deployment, monitoring, and model lifecycle management.
• Work with cloud AI/ML platforms, preferably Microsoft Azure.
• Collaborate with data engineers, software engineers, architects, and product teams to productionize AI solutions.
Required Technical Skills
• Python – strong hands-on development experience.
• Machine Learning: supervised/unsupervised learning, classification, regression, clustering, recommendation systems, feature engineering, and m
📌 AI/ML Engineer (Gurugram)
🏢 TP
📍 Gurugram