Machine Learning Engineer
Core
Design, build, and maintain robust, scalable AI solutions and multi-agent systems within a DevOps environment for wealth management.
Role type
Machine Learning Engineer (AI/LLM focus)
Builds
Multi-agent systems, RAG systems, and production AI solutions
Domain
Financial Services / Artificial Intelligence
Deliverable
production ML models
Required skills
Python, TensorFlow, Pytorch, Large Language Models (LLMs), AI agents, agentic workflows, LLM orchestration, data pre-processing, feature engineering, model evaluation, statistical concepts, software development best practices
Preferred skills
None stated
Technologies
TensorFlow, Pytorch
Responsibilities
Develop and optimize machine learning and AI solutions; Create multi-agent systems and equip AI models with function/tool-calling capabilities; Design and implement RAG systems; Assess and integrate AI models (e.g. LLMs); Optimize agentic workflows and AI agents; Test and optimize system prompts and few-shot examples; Evaluate performance of ML/AI models; Collaborate with platform teams and data engineers; Participate in code reviews, testing, and debugging
