S&P Global
Base pay range
$150,000.00/yr - $230,000.00/yr
Researcher - Talent Sourcing @ S&P Global | Hiring Technology Talent in the USA, Canada & Mexico | Join Us! The Role:
AI Technical Architect
The Team:
The Data Science Center of Excellence (COE) at S&P Global delivers AI capabilities and advancements to our S&P Global Ratings products and services. The AI ML team within the COE is comprised of experts in AI ML modeling, ML engineers, data science, and data engineering teams.
Key Responsibilities:
AI Architecture Strategy:
Develop and implement AI architecture strategies, best practices, and standards to enhance AI ML model deployment and monitoring efficiency. Create architecture roadmaps and strategies for AI platforms and technology stacks.
ML Architecture Design and Development:
Design and develop custom AI architecture for batch and stream processing-based AI ML pipelines, including data ingestion, preprocessing, and scaled AI model computation, ensuring all service level agreements (SLAs) are met. Collaborate with technology and business teams in the design, development, and implementation of enterprise AI platforms.
Internal Collaboration:
Work closely with data scientists, machine learning engineers, and software engineers to ensure smooth integration of machine learning models into production systems.
Stakeholder Engagement and Collaboration:
Collaborate with business and project management stakeholders in roadmap planning and implementation efforts, ensuring technical milestones align with business requirements.
AI Infrastructure Architecture:
Oversee the design of scalable and reliable infrastructure for AI, ML, and model training and deployment.
AI Model Deployment Architecture:
Lead the architecture of AI model deployment patterns in production environments, ensuring reliability and scalability.
AI Monitoring Architecture:
Design robust monitoring systems to track model performance, data quality, and infrastructure.
Security and Compliance:
Implement security measures and compliance standards to protect sensitive data and ensure adherence to industry regulations.
Documentation:
Maintain comprehensive documentation of AI processes and procedures for reference and knowledge sharing.
Standards and Best Practices:
Ensure the use of standards, governance, and best practices in AI pipeline monitoring and ML model monitoring, adhering to model and data governance standards.
Problem Solving:
Troubleshoot complex issues related to machine learning model deployments and data pipelines, developing innovative solutions.
Thought Leadership:
Serve as a thought leader in generative AI, influencing both technical strategy and executive-level decisions.
System Development:
Build and scale production-ready AI systems that operate reliably at enterprise levels, ensuring long-term business impact.
Communication:
Exhibit exceptional presentation skills to convey technical concepts to non-technical stakeholders and adapt communication styles to various audiences.
Passion and Strategic Thinking:
Stay ahead of AI trends and leverage emerging technologies. Demonstrate strategic thinking and influence with technical and business acumen and problem-solving skills.
Occasional travel may be required.
Compensation/Benefits Information (US Applicants Only): S&P Global states that the anticipated base salary range for this position is $150,000 – $230,000. Final base salary will be based on the individual’s geographic location, experience, and qualifications for the role.
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 or Master’s degree in Computer Science, Engineering, or a related field.
Experienced professional (8+ years) as an ML engineer, architect, or lead data scientist in a distributed or cloud platform environment, with a desire to assume greater responsibilities as a leader and mentor, while remaining hands‑on.
4+ years of hands‑on experience in ML architecture design and implementation for large‑scale enterprise AI solutions and AI products.
Experience with business and product stakeholder engagement, collaborating on AI roadmap planning and implementation efforts.
Experience working in Agile frameworks and delivery methods.
Expertise in designing and developing complex data‑driven architectures for distributed computing and orchestration technology.
Experience with cloud platform and system architectures.
Proficiency with technologies for model development and ML operations.
Knowledge of DevOps, MLOps principles and practices, and experience with version control systems and CI/CD pipelines.
Strong familiarity with trends in AI and related platforms.
Additional Preferred Qualifications:
Experience contributing to research projects or similar initiatives.
Right to Work Requirements: This role is limited to persons with indefinite right to work in the United States.
Return to Work: If you have taken time out for caring responsibilities and are looking to return to work, as part of our Return to Work initiative, Restart, we encourage enthusiastic and talented returners to apply. We will actively support your return to the workplace.
#J-18808-Ljbffr
Researcher - Talent Sourcing @ S&P Global | Hiring Technology Talent in the USA, Canada & Mexico | Join Us! The Role:
AI Technical Architect
The Team:
The Data Science Center of Excellence (COE) at S&P Global delivers AI capabilities and advancements to our S&P Global Ratings products and services. The AI ML team within the COE is comprised of experts in AI ML modeling, ML engineers, data science, and data engineering teams.
Key Responsibilities:
AI Architecture Strategy:
Develop and implement AI architecture strategies, best practices, and standards to enhance AI ML model deployment and monitoring efficiency. Create architecture roadmaps and strategies for AI platforms and technology stacks.
ML Architecture Design and Development:
Design and develop custom AI architecture for batch and stream processing-based AI ML pipelines, including data ingestion, preprocessing, and scaled AI model computation, ensuring all service level agreements (SLAs) are met. Collaborate with technology and business teams in the design, development, and implementation of enterprise AI platforms.
Internal Collaboration:
Work closely with data scientists, machine learning engineers, and software engineers to ensure smooth integration of machine learning models into production systems.
Stakeholder Engagement and Collaboration:
Collaborate with business and project management stakeholders in roadmap planning and implementation efforts, ensuring technical milestones align with business requirements.
AI Infrastructure Architecture:
Oversee the design of scalable and reliable infrastructure for AI, ML, and model training and deployment.
AI Model Deployment Architecture:
Lead the architecture of AI model deployment patterns in production environments, ensuring reliability and scalability.
AI Monitoring Architecture:
Design robust monitoring systems to track model performance, data quality, and infrastructure.
Security and Compliance:
Implement security measures and compliance standards to protect sensitive data and ensure adherence to industry regulations.
Documentation:
Maintain comprehensive documentation of AI processes and procedures for reference and knowledge sharing.
Standards and Best Practices:
Ensure the use of standards, governance, and best practices in AI pipeline monitoring and ML model monitoring, adhering to model and data governance standards.
Problem Solving:
Troubleshoot complex issues related to machine learning model deployments and data pipelines, developing innovative solutions.
Thought Leadership:
Serve as a thought leader in generative AI, influencing both technical strategy and executive-level decisions.
System Development:
Build and scale production-ready AI systems that operate reliably at enterprise levels, ensuring long-term business impact.
Communication:
Exhibit exceptional presentation skills to convey technical concepts to non-technical stakeholders and adapt communication styles to various audiences.
Passion and Strategic Thinking:
Stay ahead of AI trends and leverage emerging technologies. Demonstrate strategic thinking and influence with technical and business acumen and problem-solving skills.
Occasional travel may be required.
Compensation/Benefits Information (US Applicants Only): S&P Global states that the anticipated base salary range for this position is $150,000 – $230,000. Final base salary will be based on the individual’s geographic location, experience, and qualifications for the role.
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 or Master’s degree in Computer Science, Engineering, or a related field.
Experienced professional (8+ years) as an ML engineer, architect, or lead data scientist in a distributed or cloud platform environment, with a desire to assume greater responsibilities as a leader and mentor, while remaining hands‑on.
4+ years of hands‑on experience in ML architecture design and implementation for large‑scale enterprise AI solutions and AI products.
Experience with business and product stakeholder engagement, collaborating on AI roadmap planning and implementation efforts.
Experience working in Agile frameworks and delivery methods.
Expertise in designing and developing complex data‑driven architectures for distributed computing and orchestration technology.
Experience with cloud platform and system architectures.
Proficiency with technologies for model development and ML operations.
Knowledge of DevOps, MLOps principles and practices, and experience with version control systems and CI/CD pipelines.
Strong familiarity with trends in AI and related platforms.
Additional Preferred Qualifications:
Experience contributing to research projects or similar initiatives.
Right to Work Requirements: This role is limited to persons with indefinite right to work in the United States.
Return to Work: If you have taken time out for caring responsibilities and are looking to return to work, as part of our Return to Work initiative, Restart, we encourage enthusiastic and talented returners to apply. We will actively support your return to the workplace.
#J-18808-Ljbffr