Machine Learning Engineer, AI Decisioning

Position Overview

• Location Type: Remote
• Employment Type: Full-time
• Salary: $200,000 - $260,000 USD per year (location independent)
• About the Role: Hightouch is seeking a Machine Learning Engineer to expand its data activation products with an intelligence layer. This role focuses on building comprehensive solutions to personalize messaging, automate experimentation, predict customer behavior, generate content, and optimize marketing spend, leveraging customer data from data warehouses and databases. It's a senior role emphasizing impact and potential for growth over years of experience.

Requirements

• Strong understanding of machine learning principles and techniques.
• Experience with predictive modeling and building machine learning models.
• Experience with machine learning infrastructure and deployment.
• Ability to work on customer research, problem definition, and solution design.
• Intellectual curiosity and motivation to tackle complex problems.
• Ability to partner with customers and translate business needs into technical solutions.

Responsibilities

• Build comprehensive machine learning solutions to address customer challenges in personalization, product recommendation, automated experimentation, predictive audiences, content generation, and budget optimization.
• Work on customer research to identify and define problems.
• Develop and deploy machine learning models.
• Contribute to the design and implementation of machine learning infrastructure.
• Partner with customers to understand their needs and deliver effective solutions.
• Explore and evaluate new machine learning techniques and technologies.

Interview Process

• Intro Call [15-30m]: Introductory call with a member of the recruiting team or the hiring manager to assess mutual fit.
• System Design Screen: (Details not provided in the original description)

Company Information

• Hightouch is a company focused on data activation products, helping customers sync data into their SaaS systems to automate and improve operations.
• Remote-first policy.