Machine Learning Engineer
S&P Global1 day ago
Bengaluru, India or Hyderābād, IndiaSenior
Responsibilities
- Develop, refine, deploy, and maintain production machine learning systems for Kensho products.
- Build retrieval-driven AI agents that fetch, validate, and structure data so LLM outputs are grounded in S&P Global datasets.
- Evaluate online and offline LLM-agent performance, including 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 structured and unstructured domain-specific data and subject matter experts.
- Optimize and scale ML applications for high demand, efficient resource usage, and reliable production behavior.
- Reduce technical debt and improve system reliability and maintainability.
- Scope and execute ML initiatives while collaborating with data, product, design, and engineering teams.
- Develop ML-driven functionality that improves user workflows and supports product goals.
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 (RAG) systems.
- Experience with effective coding, documentation, collaboration, and communication practices.
- Strong problem-solving skills, initiative, and adaptability in a fast-paced environment.
Benefits
- Health care coverage and wellness support.
- Generous flexible time off.
- Continuous learning and professional development resources.
- Competitive pay, retirement planning, continuing education support, company-matched student loan contributions, and financial wellness programs.
- Family-focused benefits and perks.
- Retail discounts and referral incentive awards.