Back
Tier-1 employer, popular mid-level AI role, and metro location significantly increase applicant density.
Core ML skills transfer across industries, but investor-facing research context increases domain specificity.
Explicit 3+ years plus mandatory LLM/RAG, Python, SQL, cloud, and production ML requirements raise strictness.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design and own AI-powered research applications integrating advanced AI (especially Generative AI) into investor workflows within PMGTech.
Lead the end-to-end development lifecycle from proof of concept through production, including data pipelines, backend integration, and front-end user experience.
Evaluate and implement AI models and APIs, establishing best practices for prompt engineering, safety, reliability, and production observability.
Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or equivalent.
Minimum 3 years of experience delivering machine learning, AI, and data-intensive systems with hands-on deployment of LLM workflows including RAG, prompt engineering, fine-tuning, and backend integration.
Proficiency in Python and SQL; experience with cloud platforms is preferred but not mandatory.
Strong communication skills to collaborate directly with investors and senior partners.
Experience working closely with investment researchers and portfolio managers to translate complex investment research needs into scalable AI-driven solutions.
Technical leadership with a strong product and user-centric mindset, capable of simplifying complex AI systems for intuitive investor use.
Up-to-date knowledge of generative AI developments and hands-on experience with open-source language models; familiarity with financial services or investment domain is a plus.