Machine Learning Operations Engineer I

OSTTRA•Cambridge, MA

14h•Remote

About The Position

Kensho’s MLOps team is its de facto ML platform team, working at the intersection of infrastructure and machine learning. The team partners with ML product, research and development, core infrastructure, site reliability engineering, and security teams to provide processes, tooling, and infrastructure that help ML engineers work quickly and reliably and identify production issues early. The role supports a broad range of AI projects and balances practical platform development with exploration of emerging ML and agentic technologies. The MLOps Engineer will build and support internal tools that improve the developer experience and help engineers turn research into production-ready models, agents, and products. The position involves collaborating with teams to understand their workflows and pain points, adopting and integrating useful third-party and open-source solutions, and helping establish best practices for ML and agent platforms. The position may be performed from anywhere in the United States. Travel to Kensho hubs in Cambridge, Massachusetts, or New York City will sometimes be required for team meetings or company events. The anticipated base salary range is $120,000–$140,000, and the role is eligible for an annual incentive bonus and equity plans.

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; Kensho uses EKS and managed ML services such as Bedrock and SageMaker.
Proficiency in Python.
Familiarity with software engineering best practices in an ML context.
Basic understanding of machine learning concepts, LLMs, and agents.
Ability to debug distributed systems across infrastructure, networking, and application layers.
Strong communication skills to promote 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.
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 each stage of Kensho’s ML workflow robust, auditable, and usable.
Work with ML engineers to understand their workflows, 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, and integrate them into Kensho’s platform ecosystem.
Build scalable, efficient, automated processes for model fine-tuning, reinforcement learning, and LLM and agent evaluation.
Improve observability for LLM and agentic applications in production, including monitoring for performance problems, decay, and drift.
Track emerging tools and frameworks, promote best practices, and contribute technical expertise to the team.

Benefits

Medical, dental, and vision insurance with 100% company-paid premiums.
Unlimited paid time off.
26 weeks of 100% paid parental leave, including maternity and paternity leave.
401(k) plan with 6% employer matching.
Company matching on donations to nonprofit charities.
Up to $20,000 in tuition assistance toward degree programs, plus 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.