Ai Ml Engineer

Key Responsibilities:

• Design and develop machine learning and AI models for business use cases.
• Collect, clean, preprocess, and analyze structured and unstructured data.
• Develop predictive models using supervised and unsupervised learning techniques.
• Implement deep learning models using frameworks such as TensorFlow or PyTorch.
• Build and optimize NLP, GenAI, or recommendation-based solutions as required.
• Perform model training, validation, tuning, and performance optimization.
• Deploy ML models into production using MLOps practices.
• Develop APIs and integrate AI/ML models with enterprise applications.
• Monitor model performance and continuously improve models.
• Work with Data Scientists, Data Engineers, Software Engineers, and business teams.
• Ensure scalability, reliability, security, and maintainability of AI solutions.

Mandatory Skills:

• Strong Python programming.
• Machine Learning and Deep Learning concepts.
• Experience with Scikit-learn, TensorFlow, or PyTorch.
• Strong knowledge of NLP / Generative AI / LLMs.
• Experience with SQL and data processing.
• Knowledge of ML model deployment and MLOps.
• Experience with REST APIs and Git.
• Knowledge of cloud platforms such as AWS / Azure / GCP.

Good to Have:

• Experience with LLMs, RAG, LangChain, Hugging Face, vector databases.
• Knowledge of Docker and Kubernetes.
• Experience with MLflow, CI/CD, and model monitoring.
• Knowledge of cloud AI/ML services.
• Experience building production-grade GenAI applications.

Education: