Overview
Design and develop generative AI and machine learning solutions for fixed income investment and business problems within the Global Fixed Income team.
What you'll do
- Design and develop generative AI and machine learning solutions for fixed income investment and business problems.
- Experiment with and implement generative AI techniques such as retrieval-augmented generation (RAG), embeddings, and LLM-based workflows.
- Build, train, and fine-tune machine learning and deep learning models using appropriate frameworks and methodologies.
- Analyze large structured and unstructured datasets to extract insights and engineer features.
- Apply statistical methods and hypothesis-driven experimentation to evaluate and validate model performance.
- Contribute to deployment and integration of models into production systems, including APIs and scalable pipelines.
- Communicate model outputs, insights, and recommendations to technical and non-technical stakeholders.
What you'll need
- Bachelor's or Master's degree in Computer Science/Engineering or related field.
- 4+ years of relevant experience.
- Working knowledge of machine learning foundations including linear algebra, probability, statistics, and optimization.
- Knowledge of generative AI, statistical learning, optimization, NLP, deep learning, or time series analysis.
- Proficiency in Python and SQL.
- Experience with frameworks/tools including PyTorch, TensorFlow, Scikit-learn, Hugging Face, LangChain, and LlamaIndex.
- Familiarity with cloud platforms (GCP, Azure, AWS) and version control (Git/GitHub).
Details
- Selected hybrid work model: at least 4 days in the office per week, with flexibility to work from home 1 day a week.
Read the full description and apply on the company’s own careers page.
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