BlackRock

Artificial Intelligence Engineer, Portfolio Management Group, Associate

BlackRock

Mumbai•Hybrid•4-7 Yrs•Jul 8

Hybrid

About Global Fixed Income Team

Design and develop generative AI and machine learning solutions to address 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, engineer features, and support model development
Apply statistical methods and hypothesis-driven experimentation to evaluate model performance and validate results
Work closely with portfolio managers, researchers, and business stakeholders to translate investment problems into data science solutions
Contribute to the deployment and integration of models into production systems, including APIs and scalable pipelines
Collaborate with data engineers to ensure high-quality data pipelines and efficient data access
Ensure adherence to responsible AI principles including model interpretability, fairness, and data governance
Communicate model outputs, insights, and recommendations clearly to technical and non-technical stakeholders.
Stay updated with advancements in AI, machine learning, and quantitative methods to continuously enhance solutions

Bachelor's or Master's degree in Computer Science/Engineering or related field.
4+ years of relevant experience.
Good understanding of the foundations and working principles of machine learning algorithms, linear algebra, probability theory, statistics, and optimization theory.
Knowledge of at least one of the following domains: generative AI, statistical learning, optimization, NLP, deep learning or time series analysis.
Should have strong proficiency in the following
Languages: Python, SQ
Frameworks: PyTorch, TensorFlow, Scikit-learn, Hugging Face, LangChain, LlamaInde
Data & Storage: large‑scale distributed data analytics engines, Pandas, Snowflake, FAISS, Pinecone, Chrom
Familiarity with cloud platforms (GCP, Azure, AWS
Proficiency in version control systems (e.g., Git/GitHub).
Strong analytical thinking skills with an ability to creatively solve business problems, innovating new techniques as needed.
Excellent verbal and written communication skills.
Self-driven and results oriented team player with ability to collaborate effectively across geographies/time zones
Passion for solving interesting and relevant real-world problems in Finance using a data science and AI approaches.
Prior experience in financial services or large-scale enterprise systems is a plus.

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