Lead AI/ML Engineer
S&P Global18 days ago
Base Salary
$149k - $202k/yr
Responsibilities
- Architect and own end-to-end delivery of scalable ML and Generative AI solutions from requirements definition through production deployment on AWS.
- Build reusable AI platforms, model evaluation frameworks, and performance optimization tooling for enterprise Ratings analytics.
- Apply agentic AI frameworks, LLM fine-tuning, and retrieval-augmented generation to credit ratings datasets.
- Lead technical research and adoption of emerging AI/ML technologies and improve the quality, scalability, and performance of analytics solutions.
- Partner with data scientists, software engineers, business analysts, and senior business stakeholders to deliver production-grade solutions.
- Define and champion AI engineering best practices, reusable capability frameworks, and technical standards.
- Develop production AI systems using deep learning, NLP, Generative AI, structured and unstructured data, and autonomous workflow architectures.
Requirements
- 10+ years designing, building, and deploying production-grade AI, ML, or data-driven solutions in AWS cloud environments, including end-to-end ownership through live operation.
- 5+ years of Python development and production use of TensorFlow, PyTorch, or scikit-learn in model training, evaluation, and deployment pipelines.
- 3+ years of Java application development using Spring Boot and 3+ years deploying and managing containerized workloads with Docker and Kubernetes.
- Experience delivering at least two production AI systems incorporating deep learning, NLP, or Generative AI techniques.
- Applied SQL-based management of structured and unstructured datasets at enterprise scale and hands-on experience with agentic AI frameworks or autonomous workflow architectures.
- Experience using GitHub Copilot, Cursor, or Claude Code across at least two shipped production projects.
- Preferred experience delivering agentic AI systems with LangChain, LangGraph, CrewAI, ADK, or Strands.
- Preferred 2+ years implementing graph databases or graph-based algorithms with Neo4j or Amazon Neptune.
- Preferred proficiency with React, JavaScript, or HTML for integrating ML model outputs into user-facing applications.
- Preferred 2+ years of data engineering experience involving pipeline development, feature engineering, and ML training data preparation.
- Preferred experience operating data lakes or AI-ready data platforms using AWS Lake Formation, Databricks, or Snowflake.
- Preferred experience deploying ML solutions with Apache Spark or Hadoop on datasets exceeding 1 TB.
- Preferred 2+ years applying AI-native SDLC practices including automated model evaluation, experiment tracking with MLflow or Weights & Biases, and model versioning.
Benefits
- Hybrid work arrangement requiring at least two days per week in the New York, NY office, with specific days agreed with the hiring manager.
- Health care coverage and wellness benefits.
- Generous paid time off and flexible downtime.
- Continuous learning resources and professional development support.
- Retirement planning, continuing education support, company-matched student loan contributions, and financial wellness programs.
- Family-friendly benefits, retail discounts, and referral incentive awards.
- Annual incentive plan eligibility in addition to base compensation.
Tech Stack
Apache HadoopApache SparkAWSDatabricksDockerGitHTMLJavaJavaScriptKubernetesMLflowNeo4jPythonPyTorchReactscikit-learnSnowflakeSpring BootSQLTensorFlow