Senior Machine Learning Engineer - Link
Remote
Kensho
Kensho develops cutting-edge products and technologies that transform businesses. We are the AI Innovation Hub for S&P Global.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, automated database linking, 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.
About The Role
Kensho is looking for a Senior ML Engineer to join the Kensho Link team to lead the technical evolution of the product. The Link team builds world-class solutions that map clients’ entities' data (companies, transactions, people, etc.) to unique ID numbers drawn from S&P Global’s world-class company database with precision and speed. The ideal candidate has passion for working with structured data.
What You’ll Do
- Provide technical leadership to the machine learning team working on the Kensho Link product
- Partner with Product manager to develop a future vision for the product
- Organize team’s work by translating product goals into technical once
- Facilitate day-to-day operations and timely delivery of a product
- Oversee and lead the work on the core capabilities that the team builds, including scoping and planning of ML projects
- Actively participate in the ML model lifecycle, from problem framing to training, deployment and monitoring in production
- Work in a cross-functional team of ML engineers, Product Managers, Designers, Backend & Frontend engineers who are passionate about their product
- Mentor and lead other ML Scientists and Engineers to help make our team even more awesome!
Who You Are
-
Outstanding people come from all different backgrounds, and we’re always interested in meeting talented people! Therefore, we do not require any particular credential or experience. If our work seems exciting to you, and you feel that you could excel in this position, we’d love to hear from you.
- Have 5+ years of significant, hands-on experience designing, building, evaluating, and maintaining robust and scalable production ML systems
- Experience with scoping and planning of ML projects
- Exercise strong communication skills and can effectively express even complicated methods and results to a broad, often non-technical audience
- Excellent understanding of an ML-based product lifecycle
- Comfortable with modern tools for building ML pipelines, including data processing, training, inference, and evaluation
- Proficiency in Python
- Have led initiatives from the ideation stage to implementation
- [optional] Experience developing search or recommender systems
- [optional] Experience working with databases and other datastores
That said, most successful candidates will fit the following profile, which reflects both our technical needs and team culture:
Technologies We Love
- ML: LightGBM, XGBoost, DVC, Weights & Biases
- Deployment: Airflow, Docker, Kubernetes, AWS
- Datastores: Postgres, SQLite, S3, Elasticsearch
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Airflow AWS Classification Data visualization Docker Elasticsearch Excel Kubernetes LightGBM Machine Learning NLP Pipelines PostgreSQL Python Recommender systems 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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