Machine Learning Engineer delivering real - world impact through efficient, adaptive ML systems in production. Collaborating with strategic partners and directly impacting AI research and product vision.
About the role
- Associate Director leading machine learning engineering solutions for AI-powered supply chain at S&P Global Mobility. Collaborating with teams to deliver technical solutions and data processing workflows.
Responsibilities
- Design, develop, and deploy scalable machine learning pipelines and data processing workflows to support AI-powered supply chain intelligence solutions.
- Build and maintain robust ETL/ELT processes using cloud-native data services to ingest, transform, and manage large-scale datasets from diverse sources.
- Develop and optimize data models and schemas for relational data stores and graph-oriented data stores to enable efficient querying and analysis.
- Collaborate with AI/ML teams to implement and productionize machine learning models, ensuring seamless integration with data pipelines.
- Monitor and optimize the performance of data pipelines and ML workflows, applying best practices for data quality, reliability, observability, security, and scalability.
- Work closely with cross-functional teams in an Agile environment to deliver data solutions that drive business value and enhance product capabilities.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related technical field.
- 12 years of hands-on experience in data engineering, machine learning engineering, or related roles.
- Strong programming skills in a modern, general-purpose language commonly used for data and ML workloads.
- Experience with distributed data processing frameworks and in-memory data analysis libraries.
- Hands-on experience with cloud platforms and their data services, including data lakes, data warehouses, and managed database services.
- Experience with ETL/ELT development and workflow orchestration platforms for scheduling, dependency management, retries, and monitoring.
- Proficiency in SQL and experience working with relational databases and non-relational databases (e.g., document, key-value, wide-column).
- Strong problem-solving abilities with attention to detail and data quality.
- Excellent communication and collaboration skills to work effectively in cross-functional Agile teams.
- Ability to work independently and manage multiple priorities in a fast-paced environment.
- Experience with machine learning frameworks and practical understanding of MLOps practices, such as model versioning, reproducible training, automated evaluation, and controlled deployment/rollback.
- Familiarity with graph data stores and knowledge graph concepts (entities, relationships, ontologies, lineage).
- Experience with containerization technologies and container orchestration platforms for deploying and scaling services and pipelines.
- Knowledge of Infrastructure as Code approaches and CI/CD pipelines to automate testing, security checks, and deployments across environments.
Benefits
- 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.
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