Full-Time

Machine Learning Engineer 2

Kensho

Kensho

51-200 employees

AI and ML for financial analytics

Compensation Overview

$140k - $180k/yr

+ Annual incentive bonus + Equity plans

Cambridge, MA, USA + 1 more

More locations: New York, NY, USA

In Person

Bachelor's, Master's

Category
Software Engineering (1)
Required Skills
LLM
Streamlit
Scikit-learn
FastAPI
Python
Grafana
Airflow
Jupyter
PyTorch
Xgboost
Apache Spark
Machine Learning
Postgres
Docker
Matplotlib
AWS
Pandas
LangGraph
Jenkins

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Requirements
  • A bachelor's degree or higher in Computer Science, Engineering, or a related field is required.
  • At least 3 years of significant, hands-on industry experience with machine learning, natural language processing, and information retrieval systems is required.
  • Experience with all stages of the machine-learning life cycle, including designing, experimenting, deploying, and maintaining production systems, is required.
  • Strong proficiency in Python and a solid understanding of software-development best practices are required.
  • Experience with machine-learning libraries and frameworks for agent orchestration, such as LangGraph and pydanticAI, is required.
  • Experience in agentic design, understanding user interactions, and evaluating agent performance is required.
  • Effective coding, documentation, collaboration, and communication habits are required.
  • Strong problem-solving skills and a proactive approach to addressing challenges are required.
  • Ability to adapt to a fast-paced and dynamic work environment is required.
Responsibilities
  • Solve challenges in agentic design and large language model orchestration, including context engineering, data access patterns, memory management, and evaluation of agent performance.
  • Participate in all stages of the machine-learning life cycle, from problem framing and data exploration through model experimentation, deployment, and production monitoring.
  • Apply advanced natural language processing techniques to proprietary unstructured and structured datasets to extract insights and build solutions that drive business value.
  • Work with Data, Product, Design, and Engineering teams to design and develop agents that enhance user experiences and meet business objectives.
  • Collaborate with the Machine Learning Operations team to create automated solutions for the entire machine-learning systems life cycle, from technical design through implementation.

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, Massachusetts

Founded

2013

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Simplify Jobs

Simplify's Take

What believers are saying

  • September 3, 2026 added remote MCP support, expanding distribution through agentic AI tools.
  • Kensho MCP Apps beta and Figure Extraction deepen product breadth across research workflows.
  • S&P Global’s Cohere partnership and AI Data Portal increase enterprise reach for Kensho data.

What critics are saying

  • S&P Global’s July 2026 reorg makes Kensho a delivery layer, not an autonomous business.
  • Bloomberg, LSEG, and FactSet bundle AI into entrenched workflows, compressing Kensho pricing power.
  • If S&P Global standardizes AI data access, Kensho’s standalone identity disappears by 2027.

What makes Kensho unique

  • S&P Global’s trusted datasets power Kensho’s deterministic and adaptive AI retrieval layers.
  • Kensho now embeds directly inside Claude and MCP workflows, reducing friction for analysts.
  • Kensho Link reaches 70 million entities, spanning multilingual mapping across public and private companies.

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Benefits

Health - 100% employer-paid insurance that covers you and your family... and more

Wellness - 26 weeks paid parental leave, flexible work hours... and more

Growth - 6% 401K match, 20K tuition reimbursement, Knowledge Days... and more

Growth & Insights and Company News

Headcount

6 month growth

17%

1 year growth

17%

2 year growth

17%
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