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Machine Learning Engineering Manager - Document Intelligence

Machine Learning Engineering Manager - Document Intelligence
127,000 - 201,000
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Job Description

Kensho is a 100-person AI and machine learning company, centered around providing cutting-edge solutions to meet the challenges of some of the largest and most successful businesses and institutions. Our toolkit illuminates insights by helping the world better understand, process, and leverage messy data. Specifically, our solutions largely involve natural language processing (NLP) and include speech recognition (ASR), entity linking (NED), structured document extraction, record linkage, text classification, and more. We are continuously expanding our portfolio and are looking for passionate researchers to help us build and deploy state-of-the-art models across a variety of domains!

At Kensho, we believe in flexibility-first, and give our employees the opportunity to work from where they feel most productive and engaged (must be in the United States). We also value in-person collaboration, so there may be times when travel to one of our Kensho hubs (NY/DC/MA) will be required for team meetings or company events.

Our Document Intelligence team is a group of outstanding ML practitioners that aims to extract, structure, and understand the information contained inside unstructured documents.

The team is building state-of-the-art ML solutions for a wide range of complex problems, including information extraction from document text and tables, document layout analysis, optical character recognition (OCR), and more. These solutions power our customers’ data operations (including S&P Global’s), and serve as the foundation for Kensho’s natural language processing products, such as NERD and Classify.

The Document Intelligence team works closely with the Data, Product, Backend & Frontend teams, and has the full support of our ML operations and Infrastructure teams.

As a Machine Learning Engineering Manager you will be responsible for driving machine learning efforts as they relate to applied research and productionizing machine learning models to power Document Intelligence solutions. You will ensure the team is making measurable progress towards their goals, engaged & maintaining a healthy velocity, and you’ll provide technical insights and contributions to the team as well.


What You'll Do:

  • Manage a dedicated team of Applied ML scientists and ML engineers who design, build and maintain state-of-the-art ML capabilities that power Kensho Extract and other document understanding products

  • Ensure that the team builds production-ready modeling code that can be scaled out to large volume of data

  • Apply creative thinking to solve complex modeling problems

  • Collaborate with the product, go-to-market, and engineering leaders to define the team’s strategic vision and the most promising problems to go after

  • Grow, mentor, coach and develop your team members both professionally and technically

  • Partner with our talent acquisition team to hire Applied ML scientists and ML engineers to expand the team

  • Be ready to do hands-on work at up to 50% of your capacity, as well as give insightful code reviews and suggestions to the senior team members

Who You Are:

  • Have 5+ years of industry experience designing, building, evaluating, and maintaining robust and scalable production ML systems for document understanding, information retrieval, OCR, or a related domain

  • Have 2+ years of management experience

  • Have experience mentoring and/or building a team of engineers. We are looking for someone who can think long term about hiring and training

  • Have experience partnering with a product manager

  • Have a deep understanding of modern ML system design, from problem framing to deployment and monitoring in production

  • An innovation oriented person who can come up with out-of-the-box solutions

  • A thoughtful and collaborative code reviewer and teammate

  • A highly organized and result-oriented

  • Measure your professional success by your team’s success

Technologies We Love:

  • ML: PyTorch, DGL, HuggingFace, XGboost, Weights & Biases

  • ML models: graph neural nets, document-aware transformer models (LayoutLM, DETR), object-detection image models (Detectron)

  • Deployment: Airflow, Docker, AWS


At Kensho, we pride ourselves on providing top-of-market benefits, including:

  •   Medical, Dental, and Vision insurance 

- 100% company paid premiums

  •   Unlimited Paid Time Off
  •   26 weeks of 100% paid Parental Leave (paternity and maternity)
  •   401(k) plan with 6% employer matching
  •   Generous company matching on donations to non-profit charities
  •   Up to $20,000 tuition assistance toward degree programs, plus up to $4,000/year for ongoing professional education such as industry conferences
  •   Plentiful snacks, drinks, and regularly catered lunches
  •   Dog-friendly office (CAM office)
  •   In-office gyms and showers (CAM, DC)
  •   Bike sharing program memberships
  •   Compassion leave and elder care leave
  •   Mentoring and additional learning opportunities
  •   Opportunity to expand professional network and participate in conferences and events 

About Kensho

Kensho is an Artificial Intelligence company that builds solutions to uncover insights in messy and unstructured data that enable critical workflows and empower businesses to make decisions with conviction.

Kensho was founded in 2013 and was acquired by S&P Global in 2018. Kensho continues to operate as a startup in order to maintain our distinct, independent brand and to promote our breakthrough, innovative culture. Our team of Kenshins enjoy a dynamic and collaborative work environment that runs autonomously from S&P Global, while leveraging the unparalleled breadth and depth of data and resources available as part of S&P Global. As Kenshins, we pride ourselves on maintaining an innovative culture that depends on diversity and inclusion.

We are an equal opportunity employer that welcomes future Kenshins with all experiences and perspectives. Kensho is headquartered in Cambridge, MA, with offices in New York City, and Washington D.C. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin.

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