AI/ML Subject Matter Experts

We are seeking AI/ML Subject Matter Experts (SMEs) with deep technical expertise to lead and drive innovation across critical projects. Ideal candidates will bring hands-on experience in AI/ML model development, deployment, and advanced research, particularly in secure and controlled environments.

Key Responsibilities:

• Provide expert knowledge and leadership in the development and implementation of AI/ML solutions within the organization.
• Stay updated with the latest trends in AI/ML and apply cutting-edge techniques to solve complex business challenges.
• Act as a technical advisor and thought leader on AI/ML projects, guiding model design, development, and deployment.
• Collaborate with cross-functional teams to gather requirements and build tailored AI/ML solutions.
• Research, evaluate, and recommend new AI/ML technologies and methods for adoption.
• Mentor and train junior team members on best practices and AI/ML technologies.
• Lead the development, testing, and fine-tuning of AI/ML models ensuring performance meets organizational standards.
• Ensure that AI-generated outputs cite original source documents to maintain transparency.

Special Project Requirements:

LLM Fine-Tuning:

• Fine-tune pre-trained open-source LLMs, or simulate fine-tuning using adapters (LoRA) if compute resources are limited.

RAG Pipeline:

• Implement Retrieval-Augmented Generation (RAG) pipelines to enhance LLM outputs with external data retrieval.
• Employ Graph RAG techniques (multi-hop retrieval) for complex retrieval needs.

Deployment:

• Host applications locally or simulate private cloud deployment.
• No exposure of inference APIs to the public (simulate air-gapped environments if necessary).

Security Measures:

• Encrypt all data storage and retrieval paths.
• Simulate secure access measures like heartbeat monitoring or biometric authentication for highly secure apps.

API/Backend Development:

• Provide REST APIs to enable access to LLM outputs and retrieval engines.

UI/UX:

• Build a simple, intuitive user interface to demonstrate functionality and improve user experience.

Cost Awareness:

• Demonstrate cost control strategies such as model quantization, optimized retrieval pipelines, and minimal GPU usage for efficiency.

Source Attribution:

• Ensure every AI-generated answer cites its corresponding source documents for traceability.

Technical Skills Required:

• Strong background in AI/ML and deep understanding of machine learning algorithms and techniques.
• Proficiency in Python, R, or Java for AI/ML development.
• Hands-on experience with LLMs, RAG pipelines, secure deployment practices, and API development.
• Familiarity with cost-optimization methods for hosting AI solutions.