Machine Learning Expert
Exp: 14+ Years
Must Have:
Strong background within machine learning
Everything within AI starts here
Strong within Python (not looking for a software developer who has learned how to use models. Instead, looking for a core math background, machine learning, data model extraction and/or trading models)
Pytorch
Langchain
Core AI tools
Document extraction experience and comfortable enhancing the model to produce better extraction
RAG experience is a must
Agentic workflows experience
Ability to orchestrate workflows of a system. Someone who has applied their knowledge into applying agentic workflows - move through steps from beginning to end. Do transformation on it and produce a result
LLM OPS
Not looking for a software dev who learned how to use models
Building production systems and not just trying to learn something
Someone who has applied knowledge into how effectively they can apply agentic workflows
Must have professional experience working with a live system, opposed to someone doing this recreationally
Financial services is a huge plus
Plus:
Engineering experience front to back
Build workflows, examine systems, suggest solutions to it using data flows and gen AI, etc
Fixed income or institutional lending domain experience
Experience working in regulated environments with strong audit and control requirements
Familiarity with enterprise security, data governance, and entitlement models
Experience designing reusable internal platforms or shared developer tooling
Frontend experience is beneficial (Angular or React)
D2D;
Design and evolve reusable GenAI workflows used across lending business lines
Develop an enterprise grade AI-based document ingestion and data extraction capability, including traceability, confidence scoring, and human-in-the-loop review
Build AI-powered assistants embedded in lending systems using agentic workflows
Deliver automated content and deck generation workflows for reporting and approvals
Provide expert advice on GenAI architecture including model selection, orchestration patterns, and evaluation strategy
Establish LLMOps practices: extraction accuracy, assistant reliability, prompts management, and audit monitoring
Design and implement controls for entitlements, PII handling within open-source models in a regulated environment
In the role you are expected to act as a hands-on technical expert, and it has a clear path to becoming a platform owner responsible for shared GenAI standards across lending
Misc:
They do not have this type of candidate on team today - they need this candidate to come in and be a SME on the team and be confident enough to bring their own two sense into the role
AI platform is being built from scratch
Need this candidate to bring knowledge of how to chain workflows and how to enhance extractions
Stakeholders
Strats (heavy math background) + Operations users + Business users
Current volume of documents: Lending volume is massive
Docs can go from 1 page to 300+ pages (PDFs)
Redflags:
Developer who simply is using AI
Ideal Candidate:
Applied AI SME - how can come in and say "This is how it needs to be done, this is what I will need to do it, this is my timeline, etc."
Practitioner is someone who not just someone giving out straight answer