We are seeking a highly skilled and intellectually curious AI/ML Engineer with 4+ years of hands-on experience in machine learning, NLP, and large language models (LLMs). The ideal candidate should be technically strong, deeply analytical, and an excellent communicator, capable of owning complex AI/ML initiatives end-to-end. You will work at the intersection of AI engineering, generative AI, and intelligent agent systems, leveraging modern AI tools, frameworks, and cloud platforms to design cutting-edge enterprise solutions.
Key Responsibilities
Design, develop, and optimize AI/ML models (classical ML, deep learning, and LLM adaptation).
Build and evaluate NLP and neural network architectures for summarization, classification, reasoning, and context understanding.
Implement LLM use cases such as prompting strategies, fine-tuning, RAG (Retrieval-Augmented Generation), and guardrails.
Develop and deploy agentic AI flows using frameworks like LangGraph, LangChain, ADK (Agent Development Kit), and LLM Mesh.
Experiment with Claude Code Agent, RAF (Reasoning & Acting Frameworks), and MCP (Model Context Protocol) servers for orchestrated automation.
Work with the latest development tools and ecosystems: IDEs (Cursor AI, Lovable, UV Python package), Databases (Supabase, vector DBs like Pinecone, FAISS, Weaviate), Generative AI & Orchestration (LangChain, agentic pipelines, prompt engineering).
Deploy and optimize AI solutions on GCP/AWS ensuring scalability, reliability, and low latency.
Collaborate with cross-functional teams to translate enterprise use cases into production-grade AI applications.
Contribute to experimentation, benchmarking, documentation, and best practices in AI/ML development.
Required Skills & Experience
4+ years of proven experience in AI/ML model design and deployment.
Strong proficiency in Python and latest libs trend like UV package etc
Deep expertise in ML, NLP, neural networks, transformers, embeddings, and LLMs (prompting, fine-tuning, context handling).
Practical experience with LangChain, LangGraph, ADK, and agentic AI frameworks.
Hands-on experience using Cursor IDE, Supabase, and modern development environments (V0, Lovable, etc.).
Understanding of data engineering workflows (ETL, data prep, structured/unstructured data management).
Solid exposure to GCP/AWS cloud ecosystems and MLOps practices (CI/CD, deployment, monitoring).
Strong analytical thinking, structured problem-solving, and excellent verbal and written communication skills.
Nice to Have (Preferred Skills)
Experience with multi-agent systems, orchestration frameworks, and code agents.
Prior experience in building enterprise-scale AI/ML and generative AI solutions.
Familiarity with Claude, OpenAI APIs, LlamaIndex, vector databases, and LLM optimization techniques.
Understanding of ethical AI, bias mitigation, and model interpretability practices.
* Exposure to MCP integration, LLM Mesh, and agentic architecture design.
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