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At Moody's, we unite the brightest minds to turn today’s risks into tomorrow’s opportunities. We do this by striving to create an inclusive environment where everyone feels welcome to be who they are—with the freedom to exchange ideas, think innovatively, and listen to each other and customers in meaningful ways. Moody’s is transforming how the world sees risk. As a global leader in ratings and integrated risk assessment, we’re advancing AI to move from insight to action—enabling intelligence that not only understands complexity but responds to it. We decode risk to unlock opportunity, helping our clients navigate uncertainty with clarity, speed, and confidence.
Job Responsibility:
Design and deploy end to end AI and machine learning solutions including machine learning and graph-based models, natural language processing (NLP) models, and large language model (LLM) based AI agents
Build robust pipelines for data ingestion, feature engineering, model training, validation, and real-time or batch inference
Develop and integrate large language model (LLM) applications using techniques such as fine-tuning, retrieval-augmented generation, and reinforcement learning
Build autonomous agents capable of multi-step reasoning and tool use in production environments
Lead the full model and agent development lifecycle, from problem definition and data exploration through experimentation, implementation, deployment, and monitoring
Ensure solutions are scalable, reliable, and aligned with business goals
Advocate and implement machine learning operations (MLOps) best practices including data monitoring and tracing, error analysis, automated retraining, model and prompt versioning, business metrics monitoring, and incident response
Collaborate across disciplines and provide technical leadership, working with product managers, engineers, and researchers to deliver impactful solutions
Mentor team members, lead design reviews, and promote best practices in AI and machine learning systems development
Requirements:
5+ years of demonstrated experience building production-grade machine learning systems with measurable impacts
expertise in NLP and search and recommendation systems is preferred
Hands-on experience with large language model (LLM) applications and AI agents, including retrieval-augmented generation, prompt optimization, fine-tuning, agent design, and evaluation methodologies
familiarity with prompt optimization frameworks like DSPy is preferred
Deep expertise in machine learning models and systems design, including classic models (e.g., XGBoost), modern deep learning and graph machine learning architectures (e.g., transformers-based models, graph neural networks (GNN)), and reinforcement learning systems
Proven ability to take models and agents from research to production, including optimization for latency and cost, implementation of monitoring and tracing, and development of reusable platforms or frameworks
Strong technical leadership and mentorship skills, with a track record of growing engineers, improving team velocity through automation, documentation, and tooling, and influencing architectural decisions without direct authority
Excellent communication and strategic thinking abilities, capable of aligning technical decisions with business outcomes, navigating ambiguity, and driving cross-functional collaboration
Bachelor’s degree or higher in Computer Science, Engineering, or a related field
What we offer:
medical
dental
vision
parental leave
paid time off
a 401(k) plan with employee and company contribution opportunities
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