Senior AI/ML Engineer - NLP Models

Description:

Senior Ai/ml Engineer

Experience : 5 - 8 years

Location : Chennai

Key Responsibilities :

- Design, implement, and deploy machine learning models, particularly focusing on NLP, transformers, and LLM fine-tuning for real-world applications.

- Work with large-scale NLP models, fine-tune transformers, and build intelligent systems that can process and generate human language with high accuracy.

- Use Python, NumPy, Pandas, SciKit-Learn, TensorFlow/PyTorch to build and optimize models for performance.

- Utilize MongoDB (advanced usage) for storing and managing large volumes of unstructured data.

- Implement MLOps practices for model monitoring, retraining, and versioning to ensure continuous improvement and optimization of deployed models.

- Design and optimize scalable APIs for AI/ML model integration, ensuring high performance and low-latency processing.

- Leverage Docker, Kubernetes, and distributed processing techniques to ensure seamless deployment of models in production environments.

- Mentor junior team members, conduct code reviews, and contribute to best practices for efficient model development and deployment.

Preferred Skills :

- Experience integrating OpenAI services or Azure OpenAI into applications, including working with APIs for natural language tasks.

- Familiarity with Retrieval-Augmented Generation (RAG) architecture and LangChain framework for building LLM-powered applications.

- Experience with AI agent architectures, building intelligent systems that can autonomously solve problems and interact with users or other systems.

Qualifications :

- Bachelors or Masters degree in Computer Science, Engineering, Data Science, or a related field.

- 3-5 years of experience in AI/ML model development, deployment, and MLOps practices.

- Proficiency in Python and ML libraries (NumPy, Pandas, SciKit-Learn, TensorFlow/PyTorch), along with experience in advanced MongoDB usage.

- Familiarity with model versioning, monitoring, and continuous integration/deployment practices.

- Experience with Docker, Kubernetes, and distributed systems for scalable deployments.

- Knowledge in designing and optimizing scalable APIs to interface with AI/ML models.