Principal Machine Learning Engineer

About the Role:

Grade Level (for internal use):

12

About the Role:

We are seeking an exceptional Principal Machine Learning Engineer to join our organization at the forefront of applied AI. This is a senior individual contributor role designed for a practitioner who is equally at home architecting large-scale LLM infrastructure, building scalable python backend APIs, and driving organization wide AI transformation. You will be designing and delivering Generative AI and Agentic AI systems, setting engineering standards for building production grade ML applications, and mentor engineering teams across the organization. You will play a critical role in leading S&P’s AI-driven transformation to drive value internally and for our customers.

The Team:

You will work closely as part of a world-class AI & ML team comprised of Data Science, Machine Learning, MLOps and Data Engineers. The Agentic AI Platform & ML Engineering team is the central nervous system of our AI capabilities - a high-impact group working at the intersection of cutting-edge research and real-world product delivery. We operate with a strong engineering culture that moves fast without sacrificing quality, treats AI systems with mission-critical rigor, and obsesses over operationalization because models that aren't in production aren't delivering value.

Responsibilities and Impact:

• LLM & Generative AI Engineering: Deploy and architect production-scale LLM systems spanning frontier models (GPT-4 class), open-source variants (such as LLaMA, Mistral, Gemma), RAG pipelines, and multi-modal AI systems incorporating text, code, images, and structured data.
• Agentic AI Systems: Design and operationalize autonomous AI agents with multi-agent orchestration, tool-use capabilities, memory management, and enterprise-grade guardrails and observability strategies.
• Python & Software Engineering: Write high-performance Python code following SOLID principles, lead code reviews, build reusable AI libraries, and implement rigorous testing and CI/CD practices across all ML workloads
• Cloud & Distributed Systems: Architect cloud-native AI infrastructure with GPU cluster management, auto-scaling inference endpoints, vector databases, and cost-optimized distributed systems for high-throughput model serving, leveraging managed AI services (such as Bedrock, Azure OpenAI, Vertex AI) alongside self-hosted deployments (such as vLLM, TGI).
• Backend APIs & Systems Integration: Design production-grade RESTful and asynchronous APIs (similar to FastAPI, gRPC) exposing AI capabilities, integrate LLM services with enterprise systems, and own end-to-end performance, reliability, and security from design through production 
• MLOps & LLMOps: Implement comprehensive ML pipelines for training through monitoring tools (similar to MLflow, Kubeflow, SageMaker), establish prompt versioning and model governance practices, and instrument production systems with observability across performance and quality metrics
• DevOps & Platform Engineering: Embed AI workloads into CI/CD pipelines, champion containerization (such as Docker, Kubernetes, Helm) and GitOps workflows, define SRE practices for ML systems, and drive platform standardization for self-service AI capabilities 
• Organization-Wide AI Transformation: Advise engineering, product and business leadership on AI strategy and build-vs-buy decisions, evaluate third-party tooling, define transformation KPIs, and partner with governance teams to establish responsible AI policies and regulatory frameworks.

Compensation/Benefits Information:

S&P Global states that the anticipated base salary range for this position is $165,000 - $210,000. Final base salary for this role will be based on the individual’s geographic location, as well as experience level, skill set, training, licenses and certifications.

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.

Basic Required Qualifications: 

• 10+ years of progressive experience, with 8+ years in data science, data analytics, machine learning engineering, or similar roles. 

• Proven ability to translate complex technical concepts for non-technical audiences with clarity and impact. 

• Experience defining technical roadmaps, architecture decision records (ADRs), and engineering standards adopted across multiple teams. 

• History of mentoring senior and mid-level engineers, conducting effective technical interviews, and raising the organizational engineering bar. 

• LLM Frameworks: Extensive knowledge and experience in tools similar to LangChain, LlamaIndex, LangGraph, Hugging Face Transformers, PEFT, vLLM, Ollama, or equivalent production-grade tooling. 

• MLOps Tooling: Extensive knowledge and experience in tools similar to MLflow, SageMaker, Vertex AI, or Kubeflow — with a bias toward automation and repeatability. 

• Cloud Platforms: Deep expertise in cloud platforms such as AWS, GCP, or Azure. 

• Python: Expert-level proficiency including async programming, performance optimization, type systems, packaging, and internal library authorship. 

• Databases & Storage: Vector databases (similar to Pinecone, OpenSearch, Chroma), relational (such as PostgreSQL), NoSQL (such as Redis, DynamoDB), and object storage. 

• Containerization & Orchestration expertise in environments similar to Docker, Kubernetes, Helm. 

• Backend Development: Expertise in engineering in environments similar to FastAPI, REST design principles, async patterns, OAuth2/JWT, and API security best practices. 

• Distributed Systems: Experience with message queues (similar to Kafka, SQS), event streaming, microservices design patterns. 

Preferred Qualifications: 

• MS in Computer Science, Machine Learning, Engineering, or a related quantitative field. 

• Published open-source contributions in the environments such as LLM, GenAI, or NLP space. 

• Experience operating in regulated industries (finance, healthcare, legal) with AI compliance, auditability, and risk management requirements. 

• Contributions to enterprise AI governance frameworks, model risk management programs, or responsible AI practices development. 

• Cloud AI certifications: AWS ML Specialty, GCP Professional ML Engineer, Azure AI Engineer Associate, or equivalent. 

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[email protected]. 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 activityhere.

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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: [email protected] and your request will be forwarded to the appropriate person.  
 
US Candidates Only: Know Your Rights: Workplace discrimination is illegal

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IFTECH202.2 - Middle Professional Tier II (EEO Job Group)