ValueLabs - AI/ML Engineer - RAG/LLM

Role Overview :

We are looking for a highly skilled AI/ML Engineer with hands-on expertise in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Model Fine-Tuning. The ideal candidate will have experience building, deploying, and optimizing production-grade AI solutions while working closely with cross-functional teams to solve real-world business problems.

This role offers an opportunity to work on cutting-edge Generative AI initiatives, build scalable AI systems, and contribute to innovative products leveraging the latest advancements in AI and Machine Learning.

Key Responsibilities :

AI/ML Model Development :

- Design, develop, train, and deploy Machine Learning and Deep Learning models for business-critical use cases.

- Build and optimize AI solutions using supervised, unsupervised, and generative AI techniques.

- Perform data preprocessing, feature engineering, model selection, training, and evaluation.

LLM & Generative AI Development :

- Develop applications leveraging Large Language Models (LLMs) such as GPT, Llama, Claude, Gemini, Mistral, and other open-source models.

- Implement and optimize Prompt Engineering techniques for various business use cases.

- Fine-tune foundation models using domain-specific datasets to improve accuracy and performance.

- Evaluate model outputs and continuously improve model effectiveness.

RAG (Retrieval-Augmented Generation) Implementation :

- Design and implement RAG-based architectures using vector databases and semantic search techniques.

- Build knowledge retrieval systems integrating enterprise data sources.

- Work with embedding models, document chunking strategies, indexing, and retrieval pipelines.

- Optimize retrieval quality, latency, and response accuracy.

Production Deployment & MLOps :

- Deploy AI/ML solutions into production environments with scalability and reliability.

- Build automated ML pipelines, monitoring frameworks, and model lifecycle management processes.

- Implement model versioning, CI/CD practices, and performance tracking.

- Ensure model observability, drift detection, and continuous improvement.

Collaboration & Innovation :

- Collaborate with product managers, data engineers, software developers, and business stakeholders.

- Translate business requirements into scalable AI solutions.

- Stay updated with emerging trends in AI, LLMs, RAG frameworks, and Generative AI technologies.

- Contribute to technical discussions, architecture reviews, and innovation initiatives.

Mandatory Skills :

- Strong experience in AI/ML Model Development

- Hands-on expertise in Large Language Models (LLMs)

- Experience implementing RAG (Retrieval-Augmented Generation) frameworks

- Model Fine-Tuning and optimization experience

- Strong programming skills in Python

- Experience with PyTorch, TensorFlow, Hugging Face Transformers

- Knowledge of LangChain, LlamaIndex, Vector Databases (Pinecone, ChromaDB, Weaviate, FAISS, etc.)

- Experience with Prompt Engineering and AI Agent frameworks

- Understanding of MLOps concepts and production deployments

Preferred Skills :

- Experience with cloud platforms such as AWS, Azure, or GCP

- Exposure to Kubernetes, Docker, and scalable AI deployments

- Experience with AI Agents, Multi-Agent Systems, and Workflow Automation

- Knowledge of NLP, Deep Learning, and Generative AI evaluation techniques

- Familiarity with enterprise AI applications and knowledge management systems

Qualification :

- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Machine Learning, or a related field.

- Relevant AI/ML certifications will be an added advantage.

Ideal Candidate Profile :

- 3 to 7 years of hands-on experience in AI/ML engineering.

- Passionate about Generative AI, LLMs, and emerging AI technologies.

- Strong problem-solving and analytical mindset.

- Ability to independently own AI solutions from concept to production.

- Available to join within Immediate to 30 days

(ref:hirist.tech)