Machine Learning Engineer

Key Skills

Python Programming, Scala Programming, C++, Java Programming, Machine learning techniques, Data science techniques, SQL, Apache Hadoop, MapReduce, TensorFlow, PyTorch, R Programming

Job Description

Cherre provides investors, lenders, insurers, brokers and other large enterprises with a platform to collect, resolve, and augment real estate data from thousands of public, private, and internal sources. By providing a “single source of truth,” we empower companies to evaluate opportunities and trends faster and more accurately, while saving them millions of dollars in manual data collection and analytics costs.

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

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

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

Benefits

• Competitive Base Salary
• Equity
• Range of Healthcare Plans that start day one
• Paid Parental Leave
• Educational Credit
• Unlimited Vacation
• Flexible Work Schedule

If this opportunity sounds interesting, apply or reach out to our internal talent team. We are happy to tell you more about Cherre: the technology we work with, the problems we solve, the team we are assembling, and the culture we all contribute to. We are excited you are considering working with us and look forward to hearing from you!

“At the top of the mountain we are all snow leopards.” - Hunter S. Thompson

Cherre is an equal opportunity employer. We pride ourselves on hiring the best people for the job no matter their race, sex, orientation, nationality, religion, disability, or age.