Module Lead AI/ML

We are looking for an experienced Senior AI Engineer for the development and deployment of advanced AI solutions. The ideal candidate will have a strong background in statistics, machine learning, deep learning, and Generative AI, with experience in multi-agent frameworks and MLOps practices. An R&D-driven mindset is crucial for driving innovation and staying ahead in this rapidly evolving field.

Total Experience Expected: 04-06 years Qualifications

Key Responsibilities:

Design and implementation of Generative AI applications.

Fine-tune and optimize large language models (LLMs) for various use cases.

Develop and manage AI workflows using frameworks like LangChain, LlamaIndex, AutoGen, and CrewAI.

Ensure scalable and efficient deployment of AI models on cloud platforms (AWS, Azure, or Google Cloud).

Implement best practices in MLOps and LLMOps for continuous integration and deployment of AI models.

Develop and monitor machine learning pipelines using tools like Apache Airflow, MLflow, and DBT.

Implement Named Entity Recognition (NER) models using TensorFlow and PyTorch.

Work with multimodal LLMs and Optical Character Recognition (OCR) technologies.

Develop and deploy APIs using FastAPI.

Collaborate with cross-functional teams to integrate AI solutions into existing systems.

Engage in continuous learning and research to stay abreast of the latest developments in AI and incorporate them into projects.

Required Skills:

Strong proficiency in Python and experience with NLP techniques.

Expertise in agentic frameworks such as LangChain, AutoGen, and CrewAI.

Experience with LLM fine-tuning and creating distilled models from hosted LLMs.

Knowledge of building data pipelines for model training and deployment using tools like Apache Airflow, MLflow, and DBT.

Proficiency in TensorFlow and PyTorch for developing NER models.

Experience with multimodal LLMs and OCR technologies.

Familiarity with developing and deploying APIs using FastAPI.

Familiarity with cloud platforms (AWS, GCP, Azure) and containerization tools like Docker and Kubernetes.

Experience in creating CI/CD pipelines and implementing MLOps practices.

Demonstrated R&D mindset, including open-mindedness, persistence, critical thinking, and a commitment to continuous learning.

Strong problem-solving skills and the ability to work in agile teams.

Excellent communication and leadership abilities.