Pay
$166K–$240K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 1,394 postings in the last year. Stated ranges, not salaries paid.
New York, NY
Open 6 months, first seen by us 202 days agoCompensation/Benefits Information (US Applicants Only): S&P Global states that the anticipated base salary range for this position is $149,302 – $209,000. Final base salary for this role will be based on the individual’s geographical location as well as experience and qualifications for the role. In addition to base compensation, this role is eligible for an annual incentive plan. This role is not eligible for additional compensation such as an annual incentive bonus or sales commission plan. This role is eligible to receive additional S&P Global benefits. For more information on the benefits we provide to our employees, please click here.Read the full posting
2+ years applying AI-native SDLC practices including automated model evaluation pipelines, experiment tracking (e.g., MLflow or Weights & Biases), and model versioning within a team-based CI/CD workflow. Work Arrangement: This is a hybrid role requiring a minimum of 2 days per week in our New York, NY office. Specific in-office days are agreed with your hiring manager to support team collaboration and delivery. Right to Work RequirementsRead the full posting
Employment type in the employer’s posting: Full timeFrom the employer’s posting
Right to Work Requirements
You will join S&P Global Ratings' Data Services Team — an expert-led group at the forefront of AI/ML and Generative AI innovation, bringing deep expertise across critical Ratings data domains, technology platforms, and architectural patterns.
Architect and own the end-to-end delivery of scalable ML and Generative AI solutions — from requirements definition with senior business stakeholders through to production deployment on AWS — directly shaping S&P Ratings' next-generation analytics platform.
From the employer’s posting.
We're more than 35,000 strong worldwide—so we're able to understand nuances while having a broad perspective.
In the employer’s words · Read in context
Open 6 monthsWe first saw this posting 202 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
$166K–$240K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 1,394 postings in the last year. Stated ranges, not salaries paid.
Day 202
Up longer than most. Similar jobs usually come down between day 8 and day 76.
Well past S&P Global’s usual: its jobs come down by about day 18.
From 5,519 similar postings that came down, and 136 of S&P Global’s. Coming down is not always a hire.
28 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python Programming & ML Frameworks 5+ years of Python development with production application of at least one ML framework (TensorFlow, PyTorch, or scikit-learn) within end-to-end model training, evaluation, and deployment pipelines. - Java Engineering & Cloud Infrastructure 3+ years of Java application development using Spring Boot in microservices architectures, combined with 3+ years deploying and managing containerized workloads using Docker and Kubernetes in cloud-hosted environments, with active use of Git-based CI/CD workflows. - Production AI Systems — GenAI, NLP & Data Demonstrated delivery of at least 2 production AI systems incorporating deep learning, NLP, or Generative AI techniques, with applied SQL-based management of structured and unstructured datasets at enterprise scale, and hands-on development using agentic AI frameworks or autonomous workflow architectures.
- 2+ years of hands-on experience implementing graph databases (e.g., Neo4j, Amazon Neptune) or graph-based algorithms within data engineering or ML feature pipelines. - Working proficiency in at least one front-end technology (React, JavaScript, or HTML) demonstrated through integration of ML model outputs into a user-facing application. - 2+ years of data engineering experience including pipeline development, feature engineering, and data preparation for ML model training in a cloud environment.
- Cloud AI/ML Experience 10+ years of experience designing, building, and deploying production-grade AI, ML, or data-driven solutions in AWS cloud environments (e.g., SageMaker, Bedrock, or Glue), with end-to-end ownership from solution architecture through live operation. - Python Programming & ML Frameworks 5+ years of Python development with production application of at least one ML framework (TensorFlow, PyTorch, or scikit-learn) within end-to-end model training, evaluation, and deployment pipelines. - Java Engineering & Cloud Infrastructure 3+ years of Java application development using Spring Boot in microservices architectures, combined with 3+ years deploying and managing containerized workloads using Docker and Kubernetes in cloud-hosted environments, with active use of Git-based CI/CD workflows.
- Java Engineering & Cloud Infrastructure 3+ years of Java application development using Spring Boot in microservices architectures, combined with 3+ years deploying and managing containerized workloads using Docker and Kubernetes in cloud-hosted environments, with active use of Git-based CI/CD workflows. - Production AI Systems — GenAI, NLP & Data Demonstrated delivery of at least 2 production AI systems incorporating deep learning, NLP, or Generative AI techniques, with applied SQL-based management of structured and unstructured datasets at enterprise scale, and hands-on development using agentic AI frameworks or autonomous workflow architectures. - AI-Assisted Development Tooling Demonstrated use of AI-assisted development tools (GitHub Copilot, Cursor, or Claude Code) across at least 2 shipped production projects, integrated within a structured team-based software development lifecycle.
Responsibilities and Impact: - Architect and own the end-to-end delivery of scalable ML and Generative AI solutions — from requirements definition with senior business stakeholders through to production deployment on AWS — directly shaping S&P Ratings' next-generation analytics platform. - Design and build reusable AI platforms, model evaluation frameworks, and performance optimization tooling used across the Ratings organization, establishing the technical standards that power enterprise-wide innovation.
Basic Required Qualifications: - Cloud AI/ML Experience 10+ years of experience designing, building, and deploying production-grade AI, ML, or data-driven solutions in AWS cloud environments (e.g., SageMaker, Bedrock, or Glue), with end-to-end ownership from solution architecture through live operation. - Python Programming & ML Frameworks 5+ years of Python development with production application of at least one ML framework (TensorFlow, PyTorch, or scikit-learn) within end-to-end model training, evaluation, and deployment pipelines.
- 2+ years of data engineering experience including pipeline development, feature engineering, and data preparation for ML model training in a cloud environment. - Hands-on experience designing or operating data lakes or AI-ready data platforms (e.g., AWS Lake Formation, Databricks, or Snowflake) at enterprise scale. - Experience deploying ML solutions using Apache Spark or Hadoop on datasets exceeding 1TB in a distributed cloud environment.
- Hands-on experience designing or operating data lakes or AI-ready data platforms (e.g., AWS Lake Formation, Databricks, or Snowflake) at enterprise scale. - Experience deploying ML solutions using Apache Spark or Hadoop on datasets exceeding 1TB in a distributed cloud environment. - 2+ years applying AI-native SDLC practices including automated model evaluation pipelines, experiment tracking (e.g., MLflow or Weights & Biases), and model versioning within a team-based CI/CD workflow.
- Experience deploying ML solutions using Apache Spark or Hadoop on datasets exceeding 1TB in a distributed cloud environment. - 2+ years applying AI-native SDLC practices including automated model evaluation pipelines, experiment tracking (e.g., MLflow or Weights & Biases), and model versioning within a team-based CI/CD workflow. Work Arrangement: This is a hybrid role requiring a minimum of 2 days per week in our New York, NY office. Specific in-office days are agreed with your hiring manager to support team collaboration and delivery.
- Delivered at least 1 production or near-production agentic AI system using LangChain, LangGraph, CrewAI, ADK, or Strands. - 2+ years of hands-on experience implementing graph databases (e.g., Neo4j, Amazon Neptune) or graph-based algorithms within data engineering or ML feature pipelines. - Working proficiency in at least one front-end technology (React, JavaScript, or HTML) demonstrated through integration of ML model outputs into a user-facing application.
Complete your application on spgi.wd5.myworkdayjobs.com. The employer’s form will show what is required.
Already applied? Track this application
Yes. We’ve followed one other Lead AI/ML Engineer job there since April 2026. It came down after 43 days.
New ML Engineer postings at the employers we follow are up 10% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Grade Level (for internal use):
12The Team:
You will join S&P Global Ratings' Data Services Team — an expert-led group at the forefront of AI/ML and Generative AI innovation, bringing deep expertise across critical Ratings data domains, technology platforms, and architectural patterns. We operate with a clear mandate: to deliver the next generation of S&P Ratings' analytics infrastructure through technical rigor, collaborative innovation, and the translation of cutting-edge AI research into reliable, production-grade systems. This is a unique opportunity to help architect and shape the AI capabilities that inform credit decisions relied upon by global markets every day.
Responsibilities and Impact:
What We're Looking For:
Basic Required Qualifications:
Additional Preferred Qualifications:
Work Arrangement: This is a hybrid role requiring a minimum of 2 days per week in our New York, NY office. Specific in-office days are agreed with your hiring manager to support team collaboration and delivery.
This role is limited to persons with indefinite right to work in the United States.
Compensation/Benefits Information (US Applicants Only):
S&P Global states that the anticipated base salary range for this position is $149,302 – $209,000. Final base salary for this role will be based on the individual’s geographical location as well as experience and qualifications for the role.
In addition to base compensation, this role is eligible for an annual incentive plan. This role is not eligible for additional compensation such as an annual incentive bonus or sales commission plan.
This role is eligible to receive additional S&P Global benefits. For more information on the benefits we provide to our employees, please click here.
About S&P Global Ratings
At S&P Global Ratings, our analyst-driven credit ratings, research, and sustainable finance opinions provide critical insights that are essential to translating complexity into clarity so market participants can uncover opportunities and make decisions with conviction. By bringing transparency to the market through high-quality independent opinions on creditworthiness, we enable growth across a wide variety of organizations, including businesses, governments, and institutions.
S&P Global Ratings is a division of S&P Global (NYSE: SPGI). S&P Global is the world’s foremost provider of credit ratings, benchmarks, analytics and workflow solutions in the global capital, commodity and automotive markets. With every one of our offerings, we help many of the world’s leading organizations navigate the economic landscape so they can plan for tomorrow, today.
For more information, visit www.spglobal.com/ratings
What’s In It For You?
Our Mission:
Advancing Essential Intelligence.
Our People:
We're more than 35,000 strong worldwide—so we're able to understand nuances while having a broad perspective. Our team is driven by curiosity and a shared belief that Essential Intelligence can help build a more prosperous future for us all.From finding new ways to measure sustainability to analyzing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We are changing the way people see things and empowering them to make an impact on the world we live in. We’re committed to a more equitable future and to helping our customers find new, sustainable ways of doing business. Join us and help create the critical insights that truly make a difference.
Our Values:
Integrity, Discovery, Partnership
Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals.
Benefits:
We take care of you, so you can take care of business. We care about our people. That’s why we provide everything you—and your career—need to thrive at S&P Global.
Our benefits include:
Health & Wellness: Health care coverage designed for the mind and body.
Flexible Downtime: Generous time off helps keep you energized for your time on.
Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills.
Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs.
Family Friendly Perks: It’s not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families.
Beyond the Basics: From retail discounts to referral incentive awards—small perks can make a big difference.
For more information on benefits by country visit: https://spgbenefits.com/benefit-summaries
Global Hiring and Opportunity at S&P Global:
At S&P Global, we are committed to fostering a connected and engaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets.
S&P Global has a Securities Disclosure and Trading Policy (“the Policy”) that seeks to mitigate conflicts of interest by monitoring and placing restrictions on personal securities holding and trading. The Policy is designed to promote compliance with global regulations. In some Divisions, pursuant to the Policy’s requirements, candidates at S&P Global may be asked to disclose securities holdings. Some roles may include a trading prohibition and remediation of positions when there is an effective or potential conflict of interest. Employment at S&P Global is contingent upon compliance with the Policy.
Recruitment Fraud Alert:
If you receive an email from a spglobalind.com domain or any other regionally based domains, it is a scam and should be reported to reportfraud@spglobal.com. S&P Global never requires any candidate to pay money for job applications, interviews, offer letters, “pre-employment training” or for equipment/delivery of equipment. Stay informed and protect yourself from recruitment fraud by reviewing our guidelines, fraudulent domains, and how to report suspicious activity here.
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Equal Opportunity Employer
S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment.
If you need an accommodation during the application process due to a disability, please send an email to: EEO.Compliance@spglobal.com and your request will be forwarded to the appropriate person.
US Candidates Only: Know Your Rights: Workplace discrimination is illegal
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20 - Professional (EEO-2 Job Categories-United States of America), IFTECH202.2 - Middle Professional Tier II (EEO Job Group), SWP Priority – Ratings - (Strategic Workforce Planning)Selected passages from the saved posting. Check the full description for conditions and exceptions.
Compensation/Benefits Information (US Applicants Only): S&P Global states that the anticipated base salary range for this position is $149,302 – $209,000. Final base salary for this role will be based on the individual’s geographical location as well as experience and qualifications for the role. In addition to base compensation, this role is eligible for an annual incentive plan. This role is not eligible for additional compensation such as an annual incentive bonus or sales commission plan. This role is eligible to receive additional S&P Global benefits. For more information on the benefits we provide to our employees, please click here.
New York, NY
- 2+ years applying AI-native SDLC practices including automated model evaluation pipelines, experiment tracking (e.g., MLflow or Weights & Biases), and model versioning within a team-based CI/CD workflow. Work Arrangement: This is a hybrid role requiring a minimum of 2 days per week in our New York, NY office. Specific in-office days are agreed with your hiring manager to support team collaboration and delivery. Right to Work Requirements This role is limited to persons with indefinite right to work in the United States. Compensation/Benefits Information (US Applicants Only):
Work Arrangement: This is a hybrid role requiring a minimum of 2 days per week in our New York, NY office. Specific in-office days are agreed with your hiring manager to support team collaboration and delivery. Right to Work Requirements This role is limited to persons with indefinite right to work in the United States. Compensation/Benefits Information (US Applicants Only):