Develop algorithms to turn plant and mechanical drawings into structured data, extracting symbols, dimensions, and notes and converting customer problems into reusable technology.
About this role
Stockmark's new business SAT carries AI agents built on leading LLM and VLM techniques, such as Agentic RAG, Agentic OCR, Deep Research and knowledge graphs. Enterprise adoption is growing quickly, so proofs of concept, benchmarking and accuracy verification with customers, and continuous improvement after release, matter more. The Applied Research Engineer turns advanced AI research into customer value.
The engineer develops and improves AI agents so they work in enterprise customers' operations, and owns the full value cycle from initial proof of concept to technical verification and ongoing improvement after release. They turn customer problems into technical requirements with researchers, product managers and consultants, and implement while leading decisions. Tasks include upgrading the agents' core logic, designing and running initial PoCs, building evaluation and improvement cycles for released agents (accuracy evaluation, workflow and prompt optimisation), designing and customising agents around customer-specific needs, and feeding abstracted learnings back to the SAT product and research team.
The stack is Python, TypeScript, Docker, Terraform and AWS, Azure or Google Cloud. A publication record is not required.
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