Senior AI ML Engineer

Job Summary

As a Senior AI/ML Engineer, you will be responsible for designing, developing and deploying machine learning and deep learning solutions for real-world, production-grade applications. This role is ideal for an experienced professional with strong expertise in machine learning algorithms, deep learning frameworks and applied data science.

You will work closely with data engineers, backend developers and product teams to integrate AI/ML models into scalable systems, contribute to advanced use cases, and continuously improve model performance and reliability.

Responsibilities

• Design, build and deploy machine learning models for classification, regression, clustering, NLP and computer vision use cases.
• Perform data preprocessing, feature engineering and exploratory data analysis (EDA).
• Develop, train and optimize deep learning models using frameworks such as TensorFlow, PyTorch, Keras and Hugging Face.
• Collaborate with data engineers and product teams to integrate AI/ML solutions into production systems.
• Conduct experiments, evaluate models and apply performance tuning and optimization techniques.
• Develop AI-driven automation solutions, including AI-based trading bots, smart contract analysis and intelligent data processing systems.
• Implement NLP solutions such as chatbots, sentiment analysis and text summarization.
• Work with real-time ML inference and deploy models on cloud or edge environments.
• Implement model monitoring, logging, versioning and retraining strategies.
• Stay current with the latest research, tools and best practices in AI and machine learning.
• Contribute to documentation, design discussions and knowledge sharing within the team.

Requirements

• B.Sc. / B.E. / B.Tech / M.E. / M.Tech in Computer Science or Electronics Communication.
• MCA or relevant practical experience in lieu of formal education (Experience in blockchain-related AI use cases is an added advantage).

Experience

• 5+ years of hands-on experience in machine learning and deep learning development.
• Strong proficiency in Python and libraries such as Scikit-learn, Pandas, NumPy, Matplotlib, etc.
• Hands-on experience with deep learning frameworks: TensorFlow, Keras, or PyTorch.
• Experience with NLP or Computer Vision tools such as spaCy, NLTK, OpenCV, or Hugging Face Transformers.
• Solid understanding of supervised, unsupervised and reinforcement learning algorithms.
• Strong grasp of statistics, probability and data analysis.
• Experience with model deployment and serving using tools such as Flask/FastAPI, Docker, AWS SageMaker, or Google AI Platform.
• Familiarity with real-time inference and production ML systems.
• Strong analytical thinking and problem-solving abilities.
• Ability to collaborate effectively in cross-functional teams.

Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.