Machine Learning Operations Engineer I
S&P Global5 days ago
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 deliver effective platform solutions.
- Build scalable, efficient, automated processes for model fine-tuning, reinforcement learning, and LLM or agent evaluation.
- Improve observability for LLM and agentic applications to detect production performance issues, decay, and drift.
- Evaluate, integrate, and promote open-source and third-party solutions across Kensho’s platform ecosystem.
- Track emerging tools and frameworks and promote best practices across multiple engineering teams.
- Debug distributed systems across infrastructure, networking, and application layers.
Requirements
- At least 1 year of experience in ML infrastructure, MLOps, ML engineering, or a similar area.
- Experience with Kubernetes and understanding of AWS cloud platforms.
- Python proficiency.
- Basic understanding of machine learning concepts, LLMs, and agents.
- Familiarity with distributed computing frameworks and workflow orchestration such as Ray and Airflow is preferred.
- Experience with agentic AI systems, MCP server patterns, and evaluation pipelines is preferred.
- Ability to communicate effectively and drive adoption of tools and best practices across teams.
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.
- Tuition assistance of up to $20,000 toward degree programs and up to $4,000 annually for professional education and conferences.
- Charitable donation matching, compassion leave, elder care leave, mentoring, and learning opportunities.
- Snacks, drinks, catered lunches, dog-friendly Cambridge office, and bike-sharing memberships.
- Remote work is available from within the United States, with occasional travel required to the Cambridge or New York City hubs for meetings or company events.