Genai Ml Mlops Engineering Lead (Remote)

About the Role:

We are seeking a Lead/Associate Director of ML & MLOps Engineering – GenAI to join our ML team within the Data Science COE at S&P Global focusing on building Generative AI solutions.

You will lead the engineering activities for building production grade generative AI solutions, play a pivotal role in implementing our machine learning engineering operations to ensure the seamless deployment, monitoring, and management of our machine learning models and data pipelines.

The Team:

You will be work closely in a world class AI ML team comprised of experts in AI ML modeling, ML & LLMOps engineers, data science and data engineering teams. You will contribute to engineering and developing solutions for ML operations and be a critical part of leading S&P’s AI-driven transformation to drive value internally and for our customers.

S&P is a leader in automation and AI/ML to transform risk management. This role is a unique opportunity for ML/MLOps engineers to grow into the next step in their career journey.

Responsibilities and Impact:

• Lead ML Engineering to architect, build and deploy production grade GenAI services and solutions.
• Work on large-scale stateful and stateless distributed systems, including infrastructure, data ingestion platforms, SQL and no-SQL databases, microservices, orchestration services and more.
• Lead MLOps/LLMOps platform development & automated pipelines focusing on deploying, monitoring and maintaining models in production environments; with model governance, cost and performance optimization.
• Collaborate with cross-functional teams to integrate machine learning models into production systems.
• Create and manage Documentation and knowledge base, including development best practices, MLOps/LLMOps processes and procedures.
• Work closely with members of technology teams in the development, and implementation of Enterprise AI platform.

Compensation/Benefits Information: (This section is only applicable to US candidates)

S&P Global states that the anticipated base salary range for this position is $108,000 to $215,000. 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 eligible to receive additional S&P Global benefits. For more information on the benefits we provide to our employees, please click here.

What We’re Looking For:

Basic Required Qualifications:

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• 8+ years of progressive experience as in machine learning, data analytics or similar roles.
• 5 years of relevant experience with
• Writing production level, scalable code with Python (or scala)
• MLOps/LLMOps, machine learning engineering, Big Data, or a related role.
• Elasticsearch, SQL, NoSQL, Apache Airflow, Apache Spark, Kafka, Databricks, MLflow.
• Containerization, Kubernetes, cloud platforms, CI/CD and workflow orchestration tools.
• Distributed systems programming, AI/ML solutions architecture, Microservices architecture experience.

Additional Preferred Qualifications:

• 2-3 years of experience with operationalizing data-driven pipelines for large scale batch and stream processing analytics solutions
• Experience with contributing to open-source initiatives or in research projects and/or participation in Kaggle competitions
• 6-12 months of experience working with RAG pipelines, prompt engineering and/or Generative AI use cases.
• Experience with SageMaker and/or Vertex AI

Return to Work:

Have you taken time out for caring responsibilities and are now looking to return to work? As part of our Return to Work initiative, Restart, we are encouraging enthusiastic and talented returners to apply, and will actively support your return to the workplace.