Senior Machine Learning Engineer

March 28

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Cherre

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Real Estate • Software • AI • ML • Analytics

51 - 200

Description

• Cherre is the real estate industry's leading data management platform, powering more than $3 trillion AUM globally. Our end-to-end platform helps clients connect, transform, analyze, and act on trusted data to increase efficiencies, reduce risks, gain visibility into market trends, and make strategic moves in response to changing market conditions. • We are looking to add a Machine Learning Engineer to our team. This role will be responsible for developing products that provide ML-powered insights to our customers and integrating those applications into the Cherre tech pipeline. Candidates must have an R&D / research background as well as industry-based engineering experience deploying models into production. • The work we do at Cherre touches multiple aspects of ML - the ideal candidate should be familiar with such diverse topics as deep learning, graph algorithms, and named entity resolution. Ability to implement algorithms at scale and experience with distributed computing / big data applications is critical - our knowledge graph has billions of edges! • Responsibilities: Work within an agile fullstack scrum team to deploy ML models into production, Develop new ML-based services that enhance our data capabilities, Design and implement scalable and repeatable ML pipelines, Collaborate with data engineering to design workflows for ingesting data streams required for ML applications • Starting Goals: 30 Day - Familiar with the Cherre tech stack, Exposure to the Cherre release process, Understands company and team goals, Assigned a mini-project that they will own, 60 Day - Familiar with the existing Cherre ML pipeline, Able to start contributing PRs, Understands the types of data we ingest and common customer use cases, 90 Day - Contributing to the ML pipeline on a daily basis, Mini-project is completed

Requirements

• 2+ years software experience, preferably in an object-oriented language • 3+ year experience deploying ML models in a production environment Industry-based experience with big data / distributed computing applications • Familiarity with current NLP technologies • Languages: Python, SQL • Technologies: Airflow, Kubernetes, Docker, GCP stack • Nice to Haves: Masters degree in Computer Science / Engineering discipline, Publications / patents in the field of machine learning, Technologies: Apache Spark

Benefits

• Competitive Base Salary • Equity • Range of Healthcare Plans • Paid Parental Leave • Unlimited Vacation • Flexible Work Schedule • Compensation: $155,000-220,000/ year