:

Key Responsibilities :

- Design, develop, and deploy advanced Machine Learning and AI solutions.
- Work with deep learning architectures including CNNs, RNNs, and Transformers.
- Develop solutions using Reinforcement Learning, NLP, Computer Vision, or other domain-specific AI technologies.
- Build and optimize ML models using Python or C++.
- Develop AI applications using frameworks such as PyTorch, TensorFlow, and Hugging Face.
- Build production-grade AI systems using cloud and modern MLOps practices.
- Develop and manage scalable ML pipelines and data pipelines.
- Work with relational, NoSQL, and vector databases to support AI workloads.
- Containerize and deploy ML applications using Docker and Kubernetes.
- Implement CI/CD pipelines for automated model development and deployment.
- Optimize AI systems for performance, scalability, reliability, and production readiness.

Requirements :

- Advanced ML/AI : Deep expertise in deep learning (CNNs, RNNs, Transformers), reinforcement learning,



and domain-specific areas like NLP or computer vision.
- Engineering Excellence : Proficiency in Python or C++ and experience with frameworks like PyTorch, TensorFlow, and Hugging Face.
- Infrastructure and MLOps : Experience with cloud platforms (AWS, Azure, GCP), containerization (Docker, Kubernetes), and CI/CD pipelines for production-grade AI systems.
- Data Management : Robust background in RDBMS, NoSQL, and vector databases, as well as building robust data pipelines.

Preferred Candidate Profile :

- Strong hands-on experience in developing and deploying production-grade AI/ML systems.
- Excellent understanding of modern deep learning and ML architectures.
- Experience taking models from development to production.
- Strong problem-solving and analytical skills.
- Ability to work across data science, engineering, and infrastructure teams.

📌 AI/ML Engineer (India)
🏢 Darttag Consulting
📍 India