Ai Ml Engineer

Key Responsibilities

• Design, develop, and deploy AI/ML solutions with a focus on Generative AI and LLMs.
• Fine-tune, prompt-engineer, and optimize LLMs for domain-specific tasks.
• Leverage frameworks such as LangChain, LlamaIndex, or similar for building modular AI applications.
• Integrate LLMs with APIs, databases, vector stores, and enterprise applications.
• Evaluate and implement model deployment strategies (on-prem, cloud, serverless, or containerized environments).
• Collaborate with cross-functional teams (data engineers, product managers, software engineers) to deliver end-to-end AI solutions.
• Stay updated with the latest advancements in AI, ML, and GenAI research and propose adoption of new technologies.
• Implement MLOps best practices for continuous training, deployment, and monitoring of models in production.
• Ensure responsible AI practices, focusing on bias mitigation, data privacy, and compliance.

Required Qualifications

• 3+ years of experience in software development (Python preferred; familiarity with Java, C#, or Node.js a plus).
• 3+ years of hands-on experience in Generative AI and LLM-based development.
• Strong knowledge of AI/ML fundamentals including NLP, deep learning, embeddings, and transformers.
• Experience with LLMs (e.g., OpenAI GPT, Anthropic Claude, LLaMA, Falcon, Mistral, or similar).
• Knowledge of LangChain, LlamaIndex, Haystack, or similar frameworks.
• Familiarity with vector databases (Pinecone, Weaviate, Milvus, FAISS, Chroma).
• Hands-on experience with cloud platforms (AWS, Azure, GCP) and AI services (Bedrock, VertexAI, Azure OpenAI).
• Knowledge of MLOps tools (MLflow, Kubeflow, Weights & Biases) for model lifecycle management.
• Strong problem-solving, analytical, and communication skills.