S&P Global

Machine Learning Operations Engineer I

S&P Global
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5 days ago
Cambridge, MA, USA or New York, NY, USAEntry Level
H1B sponsor

Base Salary

$120k - $140k/yr

Responsibilities

  • Develop tools, services, and frameworks that make ML workflows robust, auditable, and usable.
  • Partner with ML engineers to identify workflow pain points and improve developer productivity.
  • Build scalable automated processes for model fine-tuning, reinforcement learning, and LLM or agent evaluation.
  • Improve observability for production LLM and agentic applications, including detection of performance decay and drift.
  • Evaluate, integrate, and promote open-source and third-party tools across Kensho’s platform ecosystem.
  • Track emerging tools and frameworks and strengthen engineering best practices across teams.

Requirements

  • At least 1 year of experience in ML infrastructure, MLOps, ML engineering, or a similar discipline.
  • Experience with Kubernetes and understanding of AWS cloud platforms, including EKS, Bedrock, and SageMaker.
  • Proficiency in Python and ability to debug distributed systems across infrastructure, networking, and application layers.
  • Familiarity with distributed computing frameworks and workflow orchestration such as Ray and Airflow is preferred.
  • Basic understanding of machine learning concepts, LLMs, and agents.
  • Strong communication skills and the ability to drive adoption of tools and best practices across multiple teams.
  • Experience with agentic AI systems, MCP server patterns, or evaluation pipelines is advantageous.

Benefits

  • Medical, dental, and vision insurance with 100% company-paid premiums.
  • Unlimited paid time off and 26 weeks of fully paid parental leave.
  • 401(k) plan with 6% employer matching and charitable donation matching.
  • Up to $20,000 in tuition assistance for degree programs and up to $4,000 annually for professional education.
  • Mentoring, learning opportunities, conference participation, catered lunches, snacks, and drinks.
  • Dog-friendly Cambridge office and bike-sharing memberships, plus compassion and elder-care leave.
  • Work from anywhere in the United States, with occasional travel required to the Cambridge, Massachusetts or New York City hubs.

Tech Stack

Apache AirflowAWSBashGitKubernetesPrometheusPythonPyTorchTerraform
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