Applied AI Engineer

$132,500 - $214,500/Yr

BlackRock - New York, NY

Full-time - Mid Level

Remote - New York, NY

Funds, Trusts, and Other Financial Vehicles

About the position

The AI Engineering team at BlackRock is responsible for shaping the AI ecosystem across the firm, focusing on building and maintaining a leading-edge AI platform that enhances productivity, client experience, and alpha generation. This role involves designing and implementing innovative AI solutions within the Aladdin technology platform, which integrates investment management processes across public and private markets. The position offers an opportunity to work with top industry professionals and contribute to financial technology innovation.

Responsibilities

• Design and build the next generation of the world's best investment management technology platform, focusing on managing various investment lifecycle processes and investment research.
• Integrate new AI services across the platform and Aladdin application ecosystem.
• Refine business and functional requirements and translate them into scalable technical designs.
• Collaborate with product engineering teams to implement comprehensive AI/ML-based solutions from start to finish.
• Apply quality software engineering practices throughout the software development lifecycle.
• Optimize the software delivery and workflow of the team.
• Work with team members in a multi-office, multi-country environment.

Requirements

• B.S./M.S. degree in Computer Science, Engineering, or a related subject area with 4+ years, or equivalent experience.
• Proficiency and hands-on experience in object-oriented programming with Java and Python.
• Proficiency in designing and building scalable APIs and Microservices.
• Experience with cloud platforms such as Azure (Preferred), AWS, or GCP.
• Ability to reverse engineer existing applications.
• Grit in the face of technical obstacles.
• Experience working in Agile development teams with excellent collaboration skills.

Nice-to-haves

• Understanding of prompt engineering and prompt tuning.
• Experience building applications using LLM frameworks such as LangChain, Llama Index, and Semantic Kernel.
• Experience with vector databases like Faiss or Chroma.
• Knowledge of ML model evaluation to ensure consistent performance with changing data.
• Familiarity with MLOps and ML model lifecycle pipelines.
• Experience with ML model training and fine-tuning.
• Familiarity with event-driven architecture and messaging frameworks like Kafka.
• Experience with NoSQL datastores like Cassandra.
• Knowledge of containerization and orchestration technologies.

Benefits

• Strong retirement plan
• Tuition reimbursement
• Comprehensive healthcare
• Support for working parents
• Flexible Time Off (FTO)