Machine Learning Operations Engineer I

S&P Global•Watertown, MA

2d•Remote

About The Position

Kensho’s MLOps team is its machine learning platform team, working across infrastructure and machine learning to give ML engineers reliable processes, tooling, and infrastructure. The team partners with ML product and research groups, as well as Core Infrastructure, SRE, and Security, to improve how ML systems are developed, deployed, and operated. Its work spans pragmatic platform development and hands-on exploration of emerging machine learning and agentic technologies. The MLOps Engineer will build and support a mature ML platform, developing internal tools that help ML engineers work efficiently and deliver production-ready models, agents, and products. The role involves improving developer experience, working across teams with different products and workflows, and investigating both infrastructure and machine learning challenges. The position may be performed from anywhere in the United States, with travel to Kensho hubs in Cambridge, Massachusetts, or New York City required at times for meetings or company events. The anticipated base salary range is $120,000–$140,000. The role is also eligible for an annual incentive bonus and equity plans. Compensation decisions depend on the circumstances of each case, and Kensho notes that hires are not typically made at or near the top of the range.

Requirements

At least 1 year of experience in ML infrastructure, MLOps, ML engineering, or a similar area.
Experience with Kubernetes.
Understanding of cloud platforms, particularly AWS.
Proficiency in Python.
Ability to debug distributed systems across infrastructure, networking, and application layers.
Excellent communication skills to drive adoption of tools and best practices across multiple teams.
Curiosity, drive, humility, and eagerness to learn across engineering disciplines.

Nice To Haves

Familiarity with distributed computing frameworks and workflow orchestration, such as Ray and Airflow.
Familiarity with software engineering best practices in an ML context.
Basic understanding of machine learning concepts, LLMs, and agents.
Experience with agentic AI systems, tools, frameworks, and workflows.
Experience with MCP server patterns.
Experience with evaluation pipelines.

Responsibilities

Develop tools, services, and frameworks that make every stage of Kensho’s ML workflow robust, auditable, and usable.
Work with ML engineers to understand their processes, identify pain points, and develop effective solutions.
Provide stable tooling that enables rapid experimentation and helps turn research into prototypes and mature products.
Evaluate, select, and promote open-source and third-party solutions, supporting adoption across teams and integration with Kensho’s platform.
Build scalable, efficient, and automated processes for model fine-tuning, reinforcement learning, and evaluation of LLMs and agents.
Improve observability for LLM and agentic applications in production to help detect performance issues, decay, and drift.
Track emerging tools and frameworks, promote best practices, and strengthen the team’s technical expertise.

Benefits

Medical, dental, and vision insurance with 100% company-paid premiums.
Unlimited paid time off.
26 weeks of 100% paid parental leave.
401(k) plan with 6% employer matching.
Company matching for donations to nonprofit charities.
Up to $20,000 in tuition assistance toward degree programs.
Up to $4,000 per year for ongoing professional education, such as industry conferences.
Snacks, drinks, and regularly catered lunches.
Dog-friendly Cambridge office.
Bike-sharing program memberships.
Compassion leave and elder care leave.
Mentoring and additional learning opportunities.
Opportunities to expand professional networks and participate in conferences and events.
Annual incentive bonus and equity plans.