Machine Learning Operations Engineer Ii

Kensho (S&P Global)

Cambridge, MA, USA
Base: $130k - $175k; bonus/equity: annual incentiv...
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2+ years ml infra or mlops experience
Kubernetes distributed systems management
Aws cloud platform proficiency
** Kensho, part of S&P Global, is seeking a Machine Learning Operations Engineer II to enhance their ML platform by developing robust processes and tooling. The ideal candidate should have a strong background in ML infrastructure, Kubernetes, and Python, and be passionate about improving the developer experience within an AI-focused environment. **

Job Summary

  • The MLOps team empowers ML engineers with state-of-the-art processes, tooling, and infrastructure to iterate quickly and build reliably.
  • Employees are supported by top-of-market benefits including unlimited paid time off, 100% company-paid parental leave, and up to $20,000 in tuition assistance.
  • The role involves shipping scalable automated processes for model fine-tuning and improving LLM and agentic observability in production.

Matching Summary

Match Score: 75

** Kensho, part of S&P Global, is seeking a Machine Learning Operations Engineer II to enhance their ML platform by developing robust processes and tooling. The ideal candidate should have a strong background in ML infrastructure, Kubernetes, and Python, and be passionate about improving the developer experience within an AI-focused environment. **

Salary

Base: $130k - $175k; Bonus/Equity: Annual incentive bonus and equity plans eligible; Benefits: Medical, Dental, Vision, 401(k) matching, PTO, Tuition Assistance

Skills & Requirements

Must-have

  • 2+ years ML infra or MLOps experience
  • Kubernetes distributed systems management
  • AWS cloud platform proficiency
  • Python programming expertise
  • Ray or Airflow workflow orchestration

Nice-to-have

  • Experience with Agentic AI systems
  • Familiarity with MCP server patterns
  • Curiosity and low-ego collaborative mindset
  • Knowledge of LLMs and agent frameworks
  • Open source tool contribution experience

Key Requirements

  • 2+ years experience in ML infra or MLOps
  • Proficiency in Python programming
  • Experience managing Kubernetes clusters
  • Understanding of AWS services like EKS and SageMaker

Work Rights

Not specified

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