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Kensho

AI and ML for financial analytics

Machine Learning Operations Engineer 1

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeRemote in USA

About the Job

Requirements

  • At least 1 year of experience in machine learning infrastructure, machine learning operations, machine learning engineering, or a similar skill set.
  • Experience with Kubernetes.
  • Understanding of AWS cloud platforms, including tools such as Amazon EKS and managed machine learning services such as Bedrock and SageMaker.
  • Proficiency in Python.
  • Familiarity with software engineering best practices in a machine learning context.
  • Basic understanding of machine learning concepts, large language models, and agents.
  • Ability to debug distributed systems across infrastructure, networking, and application layers.
  • Ability to communicate effectively to drive adoption of new tools and best practices across multiple teams.

Responsibilities

  • Iterate on Kensho’s machine learning processes by developing tools, services, and frameworks that make every stage of the machine learning workflow robust, auditable, and usable.
  • Work closely with machine learning engineers to understand their processes, identify pain points, and form effective solutions.
  • Provide engineers with stable tooling to support rapid experimentation and turn research into demonstrable prototypes and mature products.
  • Evaluate, select, and champion open-source and third-party solutions, drive adoption across teams, and integrate them into Kensho’s existing platform ecosystem.
  • Ship scalable, efficient, and automated processes for model fine-tuning, reinforcement learning, and evaluation of large language models and agents.
  • Improve observability for large language models and agentic systems to monitor production applications and detect performance, decay, and drift issues.
  • Track emerging tools and frameworks, promote best practices, and strengthen the team’s technical expertise.

Desired Qualifications

  • Familiarity with distributed computing frameworks and workflow orchestration tools such as Ray and Airflow.
  • Experience with agentic artificial intelligence systems, tools, frameworks, and workflows.
  • Experience with Model Context Protocol server patterns.
  • Experience with evaluation pipelines.

About the Company

Kensho

AI and ML for financial analytics

Kensho applies artificial intelligence and machine learning to finance and business data. Its tools analyze unstructured data, transcribe and structure audio and text, and provide analytics to reveal insights. A core offering is an LLM-ready API that lets users query S&P Global datasets using natural language and integrate with AI models like GPT and Claude. The platform combines scalable machine intelligence with data enrichment to transform enterprise information for knowledge workers, whether in government or commercial institutions. Kensho differentiates itself by using its data assets from S&P Global, a focus on financial and enterprise analytics, and a scalable API that enables natural-language querying over large datasets and structured outputs. Its goal is to help clients make data-driven decisions by turning complex data into accessible, actionable insights.

Company size
51-200
Company stage
Acquired
Total funding
$17.5M
Headquarters
Cambridge, MA
Founded
2013

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