Machine Learning Engineering Manager - Document Intelligence
Remote
Kensho
Kensho develops cutting-edge products and technologies that transform businesses. We are the AI Innovation Hub for S&P Global.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
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Airflow ASR AWS Classification DataOps Docker Engineering HuggingFace Machine Learning ML models NLP OCR PyTorch Research Unstructured data Weights & Biases XGBoost
Perks/benefits: Career development Conferences Health care Medical leave Parental leave Pet friendly Startup environment Team events Unlimited paid time off
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