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Tier-1 brand, metro location, mid-level generalist ML lead title increase applicant competition.
Specialized LLM research, fine-tuning, and publication requirements reduce cross-industry transferability.
Explicit 5+ years, MSc/PhD and top-tier publications or equivalent make filters stringent.
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Lead applied research on open-source large language models (LLMs), including evaluation, fine-tuning, and deployment for production use.
Prototype multimodal AI capabilities (voice, image, speech) to enable future user-facing products.
Design evaluation methodologies and collaborate with engineering teams to translate research into production-grade AI solutions.
5+ years of applied AI/ML experience with formal training or certification in AI/ML concepts.
Advanced proficiency in Python and ML/DL frameworks such as PyTorch and Hugging Face.
Hands-on experience with LLM evaluation, fine-tuning, and deployment.
MSc or PhD in Machine Learning, Computer Science, or related quantitative field, or equivalent applied experience.
Experienced in bridging AI research with engineering to ship production-ready prototypes in regulated environments.
Demonstrated expertise in open-source LLMs, efficient inference, and applied research with publications or notable open-source contributions.
Familiarity with financial services, particularly private banking or asset management, and considerations like data sovereignty and Responsible AI.