Gen AI

3 weeks ago


Delhi, Delhi, India Mask Manpower Full time

Job Description :

We are seeking an experienced and hands-on AI Engineer specializing in Generative AI (Gen AI) and Large Language Models (LLMs) to join our team. The ideal candidate must have a proven track record of delivering live, production-grade AI solutions-POCs and demo projects will not be considered. Experience in healthcare, biotech R&D, or financial services is highly preferred.

Key Responsibilities :

- Fine-tune and optimize Large Language Models (LLMs) for mid-to-large-scale live production-quality applications.

- Implement Retrieval-Augmented Generation (RAG) techniques to enhance LLM capabilities for enterprise use cases.

- Develop and optimize APIs for seamless integration of AI models into production environments.

- Collaborate with cross-functional teams to design, develop, and implement AI-driven solutions tailored to business needs.

- Ensure model scalability, security, and compliance with industry standards.

Required Skills and Experience :

- Experience : 3-4 years of hands-on experience with Generative AI and LLMs (Total IT experience is not a priority).

- Live Production Experience : Candidates must have deployed LLM-based solutions in real-world production environments-academic work, POCs, or demo projects will not be considered.

- Domain Expertise : Prior experience in the healthcare, biotech R&D, or financial services domain is essential.

- LLM Fine-Tuning : Demonstrated expertise in fine-tuning LLMs for live production environments.

- Retrieval-Augmented Generation (RAG) : Strong understanding of RAG techniques and their implementation in AI applications.

- API Development : Experience in developing and optimizing APIs to integrate AI models with business applications.

- Good Knowledge of Cloud like AWS , Azure for deployment part

Technical Skills :

- Proficiency in Python and relevant AI/ML libraries (PyTorch, TensorFlow, Hugging Face).

- Strong understanding of LLM architectures and their optimization techniques.

- Familiarity with cloud-based or on-premise infrastructure for AI deployments.

(ref:hirist.tech)

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