AI ML Developer

The candidate is strong in artificial intelligence (AI) development, deployment, and sustained quality. This position involves development within our custom applications and new initiatives. The candidate works with developers to integrate AI-powered solutions in existing products and new innovations. They will build automation into the enterprise system, monitor model and data quality in production, and identify opportunities for ML and AI applications.

Responsibilities:

• Create and fine tune scalable ML and Generative AI solutions for business problems.

• Use ML and Generative AI tools to label data, build, train, tune and deploy models.

• Ensure the system is scalable and capable of handling large datasets and high-demand workloads to support GenAI initiatives.

• Write code and develop intelligent user interfaces.

• Integrate with existing frameworks and platforms.

• Developing and implementing APIs that allow AI systems to interact with other components.

• Working with team members to achieve daily, weekly, and monthly targets.

• Expanding your skills by attending workshops and training sessions

• Working on different shifts

Qualifications

• Extensive software engineering experience in building high performance, large-scale ML systems.

• Possess good understanding of GANs in generating new data from existing data.

• Proficiency in deep learning frameworks (e.g., PyTorch, TensorFlow, etc.) and libraries commonly used in NLP and Generative AI.

• Experience with distributed parallel training, large-scale multi-modal foundation and generative models strongly preferred.

• Proficient in Python programming

• Modeling techniques to support the full spectrum of LLM tuning including prompt engineering, instruction tuning, Reinforcement Learning, parameter-efficient tuning, and fine-tuning strongly are preferred.

• Integrate AI systems into existing frameworks or platforms, having capabilities of interacting with other components.

• Familiarity with training multi-modal foundation models and relevant frameworks strongly preferred.

• Familiarity with cloud-based infrastructure and experience deploying large-scale machine learning models in production environments.

• Experience with Vector Database and Embeddings .