Associate Director - Machine Learning Engineer at S&P Global

Hyderabad, Telangana, India

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Financial ServicesIndustries

Requirements

Bachelor's degree in Computer Science, Engineering, or a related field
8+ years of progressive experience in machine learning, data analytics or similar roles
5 years of relevant experience with writing production level, scalable code with Python (or Scala)
5 years of relevant experience with MLOps/LLMOps, machine learning engineering, Big Data, or a related role
5 years of relevant experience with Elasticsearch, SQL, NoSQL, Apache Airflow, Databricks, MLflow
5 years of relevant experience with containerization, cloud platforms, CI/CD and workflow orchestration tools
Experience with distributed systems programming, AI/ML solutions architecture, Microservices architecture
Preferred Qualifications
2-3 years of experience with operationalizing data-driven pipelines for large scale batch and stream processing analytics solutions
Experience with contributing to open-source initiatives or in research projects and/or participation in Kaggle competitions
6-12 months of experience working with RAG pipelines, prompt engineering and/or Generative AI use cases
Experience with SageMaker and/or Vertex AI

Responsibilities

Lead ML Engineering to architect, build and deploy production grade GenAI services and solutions
Work on large-scale stateful and stateless distributed systems, including infrastructure, data ingestion platforms, SQL and No-SQL databases, microservices, orchestration services and more
Lead MLOps/LLMOps platform development & automated pipelines focusing on deploying, monitoring and maintaining models in production environments; with model governance, cost and performance optimization
Collaborate with cross-functional teams to integrate machine learning models into production systems
Create and manage Documentation and knowledge base, including development best practices, MLOps/LLMOps processes and procedures
Work closely with members of technology teams in the development, and implementation of Enterprise AI platform

Skills

Key technologies and capabilities for this role

PythonScalaMLOpsLLMOpsElasticsearchSQLNoSQLApache AirflowDatabricksMLflowContainerization

Questions & Answers

Common questions about this position

What experience level is required for this Machine Learning Engineer role?

The role requires a Bachelor's degree in Computer Science, Engineering, or a related field, plus 8+ years of progressive experience in machine learning, data analytics or similar roles, including 5 years writing production-level scalable code with Python (or Scala) and in MLOps/LLMOps.

What key technical skills are needed for this position?

Required skills include Elasticsearch, SQL, NoSQL, Apache Airflow, Databricks, MLflow, containerization, cloud platforms, CI/CD, workflow orchestration tools, and experience with distributed systems, AI/ML solutions architecture, and microservices.

What is the team structure like for this role?

You will work closely in a world-class AI ML team comprised of experts in AI ML modeling, ML & LLMOps engineers, data science, and data engineering teams.

What does the company culture emphasize in this role?

The role involves collaborating with cross-functional teams, contributing to S&P's AI-driven transformation, and working in a leader in automation and AI/ML to transform risk management, with opportunities to grow into the next step in your career journey.

What makes a strong candidate for this Associate Director position?

Strong candidates have the basic qualifications plus preferred experience like 2-3 years operationalizing large-scale data pipelines, open-source contributions or Kaggle participation, and 6-12 months with RAG pipelines, prompt engineering, Generative AI, SageMaker, or Vertex AI.

S&P Global

Provides financial information and analytics services

About S&P Global

S&P Global provides financial information and analytics to a wide range of clients, including investors, corporations, and governments. The company offers services such as credit ratings, market intelligence, and indices, which help clients understand and navigate the global financial market. S&P Global's products work by utilizing advanced data analytics and research to deliver insights that assist clients in making informed decisions and managing risks. Unlike many competitors, S&P Global has a diverse range of divisions, including S&P Global Ratings and S&P Dow Jones Indices, which allows it to cater to various financial needs. The company's goal is to support clients in driving growth while also committing to corporate responsibility and positive societal impact.

New York City, New YorkHeadquarters

1917Year Founded

IPOCompany Stage

Data & Analytics, Financial ServicesIndustries

10,001+Employees

Benefits

Health Insurance

Unlimited Paid Time Off

Professional Development Budget

401(k) Company Match

Family Planning Benefits

Employee Discounts

Risks

Integration challenges with new acquisitions like ProntoNLP may cause operational issues.

Increased competition from AI-driven platforms like Brooklyn Investment Group.

Dependence on volatile credit ratings market could impact revenue stability.

Differentiation

S&P Global integrates advanced AI tools for superior financial analytics capabilities.

The company offers comprehensive ESG solutions, meeting growing sustainability demands.

S&P Global's diverse divisions provide a wide range of financial services globally.

Upsides

Acquisition of ProntoNLP boosts data analytics and sentiment scoring capabilities.

Rising demand for ESG data enhances S&P Global's market position.

Expansion into India strengthens S&P Global's research and insights offerings.

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