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Tier-1 brand, mid-level ML role, metro location, and broad AI skill requirements increase competition.
Core ML/AI skills are transferable, but fixed-income finance domain experience increases sensitivity.
Explicit 4+ years plus mandatory ML/AI frameworks and toolset creates strict screening.
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Design and develop generative AI and machine learning solutions targeting fixed income investment and business challenges.
Build, train, fine-tune, and deploy ML/DL models using frameworks like PyTorch and TensorFlow, integrating them into production systems with scalable pipelines and APIs.
Collaborate closely with portfolio managers, researchers, and data engineers to translate investment problems into data-driven AI solutions, ensuring responsible AI practices.
Bachelor's or Master's degree in Computer Science, Engineering, or related field.
4+ years of relevant experience in AI, machine learning, or related domains.
Proficiency in Python and SQL; experience with ML frameworks such as PyTorch, TensorFlow, Scikit-learn, Hugging Face.
Familiarity with generative AI techniques (RAG, embeddings, LLMs), cloud platforms (GCP, Azure, AWS), and large-scale distributed data analytics.
Experienced in applying generative AI and advanced ML techniques specifically within financial services or large-scale enterprise environments.
Strong collaboration skills working with cross-functional teams including portfolio managers and data engineers, focusing on production-level AI deployments.
Analytical thinker capable of problem-solving in complex financial investment contexts with commitment to responsible AI and data governance.