Machine Learning Engineer
S&P Global7 days ago
Bengaluru, India or Hyderābād, IndiaMid Level / Senior
H1B Sponsor
Responsibilities
- Develop, refine, deploy, scale, and maintain production-grade machine learning systems.
- Build retrieval-driven AI agents that fetch, validate, and structure S&P Global data to ground LLM outputs.
- Evaluate LLM-based agents across performance, latency, memory usage, compute efficiency, and feature consistency.
- Build and operate ML pipelines covering data processing, training, inference, evaluation, versioning, experimentation, deployment, and monitoring.
- Work with proprietary structured and unstructured datasets and subject matter experts to develop domain understanding.
- Identify technical debt and improve system reliability, maintainability, scalability, and production behavior.
- Scope, plan, and execute ML initiatives across Kensho products.
- Collaborate with data, product, design, backend, and engineering teams to deliver ML-driven user functionality.
Requirements
- Bachelor’s degree or higher in Computer Science, Engineering, or a related field.
- At least 3 years of hands-on industry experience with machine learning, natural language processing, and information retrieval systems, including designing, shipping, and maintaining production systems.
- Strong proficiency in Python.
- Experience reading and understanding SQL databases and writing queries for specific access patterns.
- Experience building ML pipelines for data processing, training, inference, maintenance, evaluation, versioning, and experimentation.
- Experience with ML libraries or frameworks for LLM orchestration, such as LangChain.
- Preferred experience with retrieval-augmented generation systems.
- Effective coding, documentation, collaboration, and communication skills, with strong problem-solving ability and adaptability.
Benefits
- Health care coverage and wellness benefits.
- Generous paid time off and flexible downtime.
- Continuous learning resources and career-development support.
- Competitive pay, retirement planning, continuing education, company-matched student loan contributions, and financial wellness programs.
- Family-friendly benefits and perks.
- Retail discounts and referral incentive awards.