Job Description

Location(s):

  • 7 World Trade Center, 250 Greenwich Street, New York, New York, 10007, US

Line Of Business: Digital Insights OU(CAAS OU)

Job Category:

  • Engineering & Technology

Experience Level: Experienced Hire

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.

If you are excited about this opportunity but do not meet every single requirement, please apply! You still may be a great fit for this role or other open roles. We are seeking candidates who model our values: invest in every relationship, lead with curiosity, champion diverse perspectives, turn inputs into actions, and uphold trust through integrity.

In Digital Insights, we leverage rich content and workflow capabilities to comprehensively evaluate risk and support better decisions. Our flagship platform CreditView incorporates credit ratings, research and Moody’s data. It is an essential tool that helps our clients in the professional services, commercial and financial industries to conduct fundamental credit analysis. Our diverse team is made up of marketing, technology, product strategy and customer experience experts.

We are seeking a passionate and innovative Software Engineer to join our fast-paced team focused on developing cutting-edge AI technology. This role is essential in contributing to a team that has already developed the company's first client-facing Generative AI (GenAI) application, which is constantly evolving and expanding. You'll have the opportunity to work with cutting-edge technology that integrates AI, machine learning, and full-stack development, as the team continues to push boundaries and innovate further.

Key Responsibilities:

· Utilize and fine-tune Large Language Models (LLMs) as part of our applications and contribute to the architecture of Retrieval-Augmented Generation (RAG) systems.

· Collaborate on the end-to-end development of client-facing GenAI solutions, leveraging both front-end and back-end frameworks.

· Use machine learning frameworks and tools, particularly Python, to optimize and implement scalable AI solutions.

· Build full-stack applications with TypeScript and React, ensuring integration with cutting-edge machine learning systems.

· Work collaboratively with cross-functional teams to design, develop, and deploy innovative solutions.

Required Qualifications:

· 4+ years hands-on working experience with Large Language Models (LLMs): Hands-on experience with LLMs, including model fine-tuning and development.

· RAG Application Development: Experience in building Retrieval-Augmented Generation applications.

· Proficiency in Machine Learning Languages: Strong knowledge of Python and familiarity with frameworks like TensorFlow or PyTorch.

· Full-Stack Development: Experience in front-end technologies such as TypeScript, React, and knowledge of modern back-end systems.

· Cloud and Deployment: Familiarity with cloud environments, preferably AWS, for deploying machine learning models and applications.

Ideal Candidate:

· You are excited to work with cutting-edge technology and solve complex problems.

· You have a passion for AI/ML and constantly seek to push the boundaries of what’s possible.

· You are a self-driven team player who excels in a collaborative and innovative environment.

This role offers a unique opportunity to contribute to the company's only client-facing GenAI application, making a significant impact on how we leverage AI in the real world. If you’re passionate about AI and love to think outside the box, we’d love to hear from you!

For US-based roles only: the anticipated hiring base salary range for this position is $134,800 to $221,950, depending on factors such as experience, education, level, skills, and location. This range is based on a full-time position. In addition to base salary, this role is eligible for incentive compensation. Moody’s also offers a competitive benefits package, including not but limited to medical, dental, vision, parental leave, paid time off, a 401(k) plan with employee and company contribution opportunities, life, disability, and accident insurance, a discounted employee stock purchase plan, and tuition reimbursement.

Moody’s is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, sex, gender, age, religion, national origin, citizen status, marital status, physical or mental disability, military or veteran status, sexual orientation, gender identity, gender expression, genetic information, or any other characteristic protected by law. Moody’s also provides reasonable accommodation to qualified individuals with disabilities or based on a sincerely held religious belief in accordance with applicable laws. If you need to inquire about a reasonable accommodation, or need assistance with completing the application process, please email accommodations@moodys.com. This contact information is for accommodation requests only, and cannot be used to inquire about the status of applications.

For San Francisco positions, qualified applicants with criminal histories will be considered for employment consistent with the requirements of the San Francisco Fair Chance Ordinance.

This position may be considered a promotional opportunity, pursuant to the Colorado Equal Pay for Equal Work Act.

Click here to view our full EEO policy statement. Click here for more information on your EEO rights under the law. Click here to view our Pay Transparency Nondiscrimination statement. Click here to view our Notice to New York City Applicants.
Candidates for Moody's Corporation may be asked to disclose securities holdings pursuant to Moody’s Policy for Securities Trading and the requirements of the position. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.

Application Instructions

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