• Design and implement machine learning algorithms tailored to solve specific business challenges, ensuring they align with project goals.
• Collaborate with data scientists and analysts to preprocess and analyze large datasets, deriving actionable insights for model improvement.
• Optimize and fine-tune existing AI models to enhance performance and accuracy, using state-of-the-art techniques and tools.
• Conduct thorough testing and validation of AI models, ensuring robustness and reliability before deployment in production environments.

Desired Candidate Profile

• TECHNICAL SKILLS: minimum 3-4 yrs of working experience mandatory Azure AI Services: Demonstrated working experience with Microsoft Azure AI Services including Azure OpenAI, Azure Machine Learning, Azure Cognitive Services, Azure AI Search, Azure Functions, and Azure Databricks. Python Programming: Strong proficiency in Python programming, including experience with REST APIs, SDKs, asynchronous processing, data manipulation, backend development, and AI application frameworks (LangChain, LlamaIndex, Semantic Kernel, LangGraph, FastAPI). LLM & Generative AI: Deep understanding of machine learning, statistical modeling, NLP, generative AI principles, LLM application development, prompt engineering, RAG architecture, embeddings, vector databases, semantic search, and model evaluation techniques. ML Libraries & Frameworks: Advanced proficiency in ML libraries such as PyTorch, TensorFlow, Hugging Face Transformers, scikit-learn, and NLP libraries (spaCy, NLTK). Vector Databases: Experience with vector databases including FAISS, Azure AI Search, ChromaDB, and Pinecone. DevOps/MLOps: Hands-on experience with DevOps/MLOps practices and tools such as Git, Docker, Kubernetes, CI/CD pipelines, MLflow, Terraform, Azure Monitor, and Application Insights. Cloud Security & Integration: Understanding of cloud security, identity and access management, data privacy, encryption, logging, monitoring, and secure API integration patterns. AI Ethics & Governance: Awareness of ethical considerations and responsible AI practices, including fairness, accountability, transparency, bias detection, hallucination mitigation, and compliance in AI systems. KNOWLEDGE, SKILLS, & EXPERIENCE Minimum Qualifications: Bachelor's degree in Computer Science, Engineering, Artificial Intelligence, Data Science, Mathematics, Statistics, or related field; Master's degree is preferred. Microsoft Certified: Azure AI Engineer Associate (AI-102) certification is highly preferred. Minimum Experience: 3+ years of hands-on experience in designing, developing, and deploying AI/ML or Generative AI solutions in production environments. Mandatory hands-on experience with Microsoft Azure AI Services. Experience working with large-scale datasets and real-time enterprise data. Experience in financial services, banking, risk, compliance, customer service, or regulated enterprise environments is an advantage.