GenAI / Machine Learning Engineer

We are seeking a highly skilled GenAI / Machine Learning Engineer to design, develop, and deploy AI-powered solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and modern machine learning frameworks. The ideal candidate will have hands-on experience building scalable AI applications, developing ML models, and integrating Generative AI solutions into enterprise environments., * Design, develop, validate, and deploy machine learning models using supervised and unsupervised learning techniques.

• Build and optimize Generative AI applications utilizing Large Language Models (LLMs) such as GPT and Ollama.
• Develop Retrieval-Augmented Generation (RAG) pipelines for enterprise AI solutions.
• Create and maintain AI workflows using LangChain and LangGraph frameworks.
• Implement prompt engineering strategies, chain-of-thought reasoning, and model optimization techniques.
• Configure and tune LLM parameters including Temperature, Top-K, and Context Length for optimal performance.
• Develop and integrate MCP tools using FastMCP.
• Build scalable backend APIs and AI services using FastAPI and Uvicorn.
• Implement observability, monitoring, and tracing solutions using LangSmith and LangFuse.
• Design and manage vector databases and embedding solutions using PGVector and Ollama Embeddings.
• Collaborate with cross-functional teams to deploy AI/ML solutions into production environments.
• Evaluate model performance and continuously improve accuracy, reliability, and scalability.

Strong experience in Machine Learning model development, validation, and deployment.

Expertise in supervised and unsupervised learning algorithms, including:

• Regression
• Classification
• Clustering

Experience with feature engineering and model evaluation techniques.

Hands-on experience with Large Language Models (LLMs), including GPT and Ollama.

Strong understanding of:

• Temperature
• Top-K Sampling
• Context Length Management

Experience with LangChain and LangGraph.

Expertise in RAG (Retrieval-Augmented Generation) development.

Strong backend development experience with FastAPI and Uvicorn.

Experience developing MCP tools using FastMCP.

Proficiency in Prompt Engineering and Chain-of-Thought techniques.

Experience with observability tools such as LangSmith and LangFuse.

Experience with vector databases and embeddings, including PGVector and Ollama Embeddings.

Strong problem-solving and analytical skills. Preferred Skills

Experience deploying AI/ML applications in cloud environments.

Knowledge of MLOps and model lifecycle management.

Experience with Python-based AI/ML ecosystems.

Familiarity with enterprise-scale AI application development and deployment.