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S&P Global
Machine Learning Engineer | Hyderabad, IN
S&P Global
Hyderabad•On-site•1-3 Yrs•Jul 1
Job description
Overview
Grade Level (for internal use): 03Job Description
Responsibilities
- S&P Global and Anthropic Announce Collaboration to Bring Trusted Financial Data into Claude
- S&P Global Data Retrieval Agent for Gemini Enterprise | Google Cloud AI agent finder About The Role
- Enjoy building robust, production-grade ML systems end to end
- Have strong ML fundamentals, with a practical understanding of the backend and deployment work needed to run these systems in production
- Want to work across data, retrieval, modeling, and system design You will partner with ML engineers, backend engineers, and product managers to drive the next generation of Kensho's AI products.
- Bachelor's degree or higher in Computer Science, Engineering, or a related field.
- 3+ years of significant, hands-on industry experience with machine learning, natural language processing (NLP), and information retrieval systems, including designing, shipping, and maintaining production systems.
- Strong proficiency in Python.
Qualifications
- Proven experience building ML pipelines for data processing, training, inference, maintenance, evaluation, versioning, and experimentation.
- Demonstrated effective coding, documentation, collaboration, and communication habits.
- Strong problem-solving skills and a proactive approach to addressing challenges.
- Ability to adapt to a fast-paced and dynamic work environment.
- (Preferred) Experience working with RAG based system What You'll Do:
- Develop Advanced ML Systems: Create, refine, and deploy machine learning systems that solve complex business problems and power Kensho products.
- Build Retrieval-Driven AI Agents: Design AI agents that fetch, validate, and structure data from S&P datasets, ensuring answers produced by LLMs are grounded in S&P's data universe.
- Evaluate LLM-based Agents: Identify and resolve performance gaps in both online and offline settings, addressing issues such as performance, latency, memory usage, compute efficiency, and feature consistency.
- Work With Domain Specific Data: Leverage proprietary structured and unstructured datasets, deep dive to have domain understanding, work with Subject Matter Experts (SMEs).
- Scale ML Applications: Optimize and scale ML systems to support high demand, efficient resource utilization, and reliable production behavior.
- Reduce Technical Debt: Proactively identify areas of the stack that can be improved, and propose solutions that strengthen reliability and maintainability.
- Taking Initiative: Scope, plan, and execute ML initiatives that develop core capabilities across Kensho products.
- Collaborate Across Teams: Work closely with Data, Product, Design, and Engineering teams to ensure smooth operations and contribute to long-term product vision.
- Improve User Experiences: Partner with Product and Design to develop ML-driven functionality that enhances user workflows and aligns with business needs.
- Drive the ML Lifecycle: Engage in all phases of the ML lifecycle, from problem framing and data exploration to model deployment and production monitoring, ensuring continuous improvement. Technologies We Love:
- Traditional ML: Scikit-learn, XGBoost, LightGBM
- ML/Deep Learning: PyTorch, Transformers, HuggingFace, LangChain
- Deployment tools such as: Docker, Amazon EKS, Jenkins, AWS
- EDA/Visualization: Pandas, Matplotlib, Jupyter, Weights & Biases
- Tools/Toolkits: DVC, MosaicML, NVIDIA NeMo, LabelBox
- Techniques: RAG, Prompt Engineering, Information Retrieval, Data Embedding
- Datastores: Postgres, OpenSearch, SQLite, S3 What's In It For You?
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. For more information on benefits by country visit: https://spgbenefits.com/benefit-summaries
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