Kensho Technologies

HQ
Cambridge, Massachusetts, USA
Total Offices: 2
100 Total Employees
Year Founded: 2013

Offices at Kensho Technologies

Kensho Technologies is headquartered in Cambridge, Massachusetts, USA and has 2 office locations.

Hybrid Workplace

Employees engage in a combination of remote and on-site work.

Typical time on-site: Not Specified

U.S. Office Locations

HQ
Cambridge, Massachusetts, USA

Kensho is located in the heart of Harvard Square within walking distance to shops, restaurants, bars and public transportation.

New York, New York, USA

55 Water Street, New York, NY, United States, 10038

Search the 14 jobs at Kensho Technologies

5 Days Ago
Cambridge, MA, USA
Hybrid
Artificial Intelligence • Fintech • Machine Learning • Natural Language Processing • Software • Generative AI
As a Security Engineer Team Lead at Kensho, you will implement security frameworks, manage security projects, mitigate vulnerabilities, lead a team of security engineers, and establish practices for risk assessment and compliance. You will ensure network safety and develop strategies against cyberattacks, while aligning with S&P Global standards.
Artificial Intelligence • Fintech • Machine Learning • Natural Language Processing • Software • Generative AI
As a Research Scientist Intern at Kensho, you will work on impactful projects in Machine Learning and Natural Language Processing. You'll collaborate with experienced researchers, conduct and publish research, and present your findings to the company. The role emphasizes in-person collaboration, with the opportunity to work from both Cambridge HQ and New York City offices.
5 Days Ago
Cambridge, MA, USA
Hybrid
Artificial Intelligence • Fintech • Machine Learning • Natural Language Processing • Software • Generative AI
As a Research Scientist in NLP at Kensho, you will develop and deploy innovative AI solutions, focusing on areas such as long-context question-answering and alignment techniques. You'll collaborate with a team of experienced scientists to fuel innovation and publish research, while leveraging substantial computational resources for model development.