Description

Key Skills: Python, PyTorch, Hugging Face, Large Language Models, Machine Learning, Deep Learning, Fine-tuning, AI Research, Experimental Design, ML Systems

Good to Have Skills: Experience with speech and voice models, audio ML, financial services experience particularly in wealth management, private banking or asset management, familiarity with data-residency and sovereignty considerations, Responsible AI knowledge for regulated environments, and JPM-internal AI/ML infrastructure experience.

Roles & Responsibilities:

• Lead applied research into open-source LLM evaluation and deployment for cost, sovereignty, and data-residency optionality.
• Run fine-tuning work for tone, lexicon, and domain-specific tasks that are currently brittle in prompts.
• Investigate inference efficiency and tokenomics including cost-per-output, model routing, and optimisation of production inference.
• Prototype voice and image/multimodal capabilities including speech-to-text, text-to-speech, voice agents, document and image understanding.
• Design rigorous evaluation methodologies and benchmarks so research findings are measurable and reproducible.
• Partner with AI and platform engineers to productionise research outputs tied to real platform or product needs.
• Publish internal findings and raise the team's collective capability through knowledge-sharing and act as recruiting magnet.

Experience Required: 5+ years of applied experience in artificial intelligence and machine learning, hands-on experience with evaluating, fine-tuning, and deploying Large Language Models, published research in top-tier AIML venues or equivalent open-source contributions.

Education: MSc or PhD in Machine Learning, Computer Science, or related quantitative field, or equivalent applied experience

Key Skills

Education

Any Graduate