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Tier-1 brand, mid-level ML role, metro location, broad AI skillset driving high applicant competition.
Strong ML skills transferable across industries but finance domain preferences increase domain specificity to medium.
Explicit 4+ years requirement plus specific ML frameworks and production deployment expectations increases shortlisting strictness.
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Design, develop, and implement generative AI and machine learning solutions for fixed income investment and business problems.
Analyze large structured and unstructured datasets to extract insights and support model development, including deployment and integration into production systems.
Collaborate with portfolio managers, researchers, and business stakeholders to translate investment challenges into AI-driven data science solutions, ensuring responsible AI principles are upheld.
Bachelor's or Master's degree in Computer Science, Engineering, or related field.
4+ years of relevant experience in AI/ML fields.
Proficiency in Python, SQL, and machine learning frameworks like PyTorch, TensorFlow, Scikit-learn, along with knowledge of generative AI technologies (e.g., retrieval-augmented generation, embeddings, LLM workflows).
Familiarity with cloud platforms (GCP, Azure, AWS) and large-scale distributed data analytics, plus experience in version control systems (e.g., Git/GitHub).
Experienced in applying advanced generative AI and machine learning techniques specifically within financial services or related domains.
Able to work cross-functionally with investment professionals to bridge AI solutions with portfolio management challenges, indicating strong domain integration skills.
Comfortable deploying scalable, production-ready AI models and pipelines while maintaining data governance and responsible AI standards.