Build and ship AI/ML solutions using LLMs, agents, RAG, and document understanding models, alongside classic ML
Prototype quickly, validate feasibility, and turn strong POCs into production systems
Evaluate models and architectures, apply testing and guardrails to improve agent and service reliability
Research and apply emerging techniques: multimodal/document AI, agentic frameworks, synthetic data generation, and new architectural approaches
Work cross-functionally with product, R&D, and compliance teams to deliver end-to-end solutions
Contribute to scalable, secure architecture and engineering best practices for AI delivery
5+ years of experience in AI/ML engineering or applied data science with production engineering responsibilities
Strong Python skills and solid software fundamentals
Experience building production LLM-powered systems, including prompt design, embeddings, fine-tuning, RAG; agent experience is a plus
Solid ML foundations; NLP, document AI, or multimodal experience is a plus
Hands-on experience with modern AI tooling (Hugging Face, PyTorch, LangChain, LangGraph) and cloud infrastructure (AWS preferred)
Strong communication and collaboration skills; comfortable working cross-functionally with product and domain teams
BS/MS/PhD in Computer Science, Data Science, or Engineering (MS/PhD a plus)
