Artificial Intelligence Engineer, Portfolio Management Group, Associate

About This Role

Responsibilities

• Design and develop generative AI and machine learning solutions for fixed income investment and business problems.
• Implement retrieval-augmented generation, embeddings, and LLM-based workflows.
• Build, train, and fine-tune machine learning and deep learning models.
• Analyze structured and unstructured data, engineer features, and support model development.
• Use statistical methods and hypothesis-driven experimentation to evaluate and validate models.
• Translate investment problems into data science solutions with portfolio managers, researchers, and stakeholders.
• Help deploy and integrate models into production systems, APIs, and scalable pipelines.
• Collaborate with data engineers on data quality, pipelines, and efficient data access.
• Apply responsible AI principles including interpretability, fairness, and data governance.
• Communicate model outputs and recommendations to technical and non-technical stakeholders.
• Stay current with advances in AI, machine learning, and quantitative methods.

Education and Experience

• Bachelor's or master's degree in computer science, engineering, or a related field.
• 4+ years of relevant experience.
• Strong foundations in machine learning algorithms, linear algebra, probability, statistics, and optimization.
• Knowledge of at least one of generative AI, statistical learning, optimization, NLP, deep learning, or time series analysis.

Technical Skills

• Strong proficiency in Python and the listed AI, machine learning, and data technologies.
• Frameworks and libraries include PyTorch, TensorFlow, Scikit-learn, Hugging Face, LangChain, and LlamaInde as listed in the source.
• Data and storage technologies include large-scale distributed analytics engines, Pandas, Snowflake, FAISS, Pinecone, and Chrom as listed in the source.
• Familiarity with GCP, Azure, or AWS.
• Proficiency with version control systems such as Git or GitHub.

Additional Qualifications

• Strong analytical thinking and creative problem-solving ability.
• Excellent verbal and written communication skills.
• Ability to collaborate effectively across geographies and time zones.
• Passion for solving relevant real-world finance problems with data science and AI.
• Prior experience in financial services or large-scale enterprise systems is a plus.

Workplace

• BlackRock uses a hybrid work model requiring employees to work at least four days per week in the office and allowing one day per week from home.
• Some business groups may require additional office time based on role responsibilities.

Benefits

• Benefits include a retirement plan, tuition reimbursement, comprehensive healthcare, support for working parents, and Flexible Time Off.

Candidate AI Guidance

• Candidates may use AI thoughtfully to learn, prepare, and work more effectively, while interviews focus on their own experiences, thinking, and judgment.

About BlackRock