Design, implement, and optimize machine learning models and algorithms to solve complex business problems.
Work closely with cross-functional teams, including data scientists, software engineers, and product managers, to develop innovative solutions that drive business growth.
Requirements
Bachelor’s or master’s degree in computer science, Data Science, or a related technical discipline.
Total 8+ years of overall software development experience with 3+ years of hands-on experience in machine learning or AI application development, with a proven track record of delivering production-grade solutions.
Strong programming proficiency in Python, with demonstrated experience in API development using FastAPI or Flask.
Backend development experience in C# or Java is considered an added advantage.
Solid experience in developing AI solutions within the AWS ecosystem, including hands-on use of the following services: Amazon Bedrock, SageMaker, Lambda, API Gateway, and S3 etc.
Practical knowledge and implementation experience with Large Language Models (LLMs) and Generative AI frameworks, such as: LangChain, Llama Index, or custom RAG (Retrieval-Augmented Generation) architectures.
In-depth understanding of RAG systems, including embedding generation, document chunking, retrieval, and response synthesis.
Experience with vector databases (e.g., Pinecone, FAISS, OpenSearch), text embeddings, and prompt engineering is added advantage.
Strong understanding of cloud security, including OAuth 2.0-based authentication, IAM policies, and secure API design.
Familiarity with DevOps practices and tools, including CI/CD pipelines, Docker, and Infrastructure as Code (IaC) tools such as CloudFormation, AWS CDK, or Terraform.
Proficiency in relational databases (e.g., SQL) and data modelling.
Solid grasp of machine learning algorithms and techniques, including deep learning architectures.
Skilled in data preprocessing, feature engineering, and data manipulation using modern data science tools and libraries.
Demonstrated experience working across the full AI/ML project lifecycle — from business requirements analysis to model deployment and productization.
Strong analytical and problem-solving skills, with a structured approach to debugging and optimization.
Excellent communication and collaboration abilities, with experience working in cross-functional and agile teams.
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.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
machine learningAI application developmentPythonAPI developmentFastAPIFlaskC#JavaAWSLarge Language Models