Machine Learning Engineer

A company empowering everyone to take action on their data is trusted by hundreds of organizations—including Autotrader, Calendly, Cars.com, Monday.com, and PetSmart—to drive business growth.

They pioneered the Composable Customer Data Platform (CDP), enabling companies to collect, prepare, and activate customer data directly from their data warehouses. Their new AI Decisioning platform goes a step further—allowing marketers to set goals and constraints that AI agents use to personalize 1:1 customer interactions. Traditionally, only technical teams could access and use customer data; now, business users across the org can personalize experiences, improve marketing performance, and act quickly using data and AI.

The team is focused on making meaningful impact for customers. They move fast, solve problems from first principles, and maintain a culture of kindness and collaboration. Ideal candidates are strong communicators with a growth mindset and a high level of motivation and persistence.

Headquartered in San Francisco with a globally distributed team, the company recently raised a Series C round at a $1.2B valuation. They’re backed by top investors including Sapphire Ventures, Amplify Partners, ICONIQ Growth, Bain Capital Ventures, Y Combinator, and Afore Capital.

About the Role

The company is hiring a Machine Learning Engineer to help expand their data activation platform with an intelligence layer. While many companies already rely on the platform to sync customer data into SaaS tools, there’s a large opportunity to improve how businesses decide which customers to target, what content to use, and when to engage. Today, this is often done through guesswork—machine learning can unlock a step-change in performance.

With deep access to customer data warehouses, this platform is uniquely positioned to power these intelligence-driven workflows.

Example Problem Areas You’ll Tackle

• Personalization & Product Recommendations: Surface the most relevant message content or product from a large option set
• Automated Experimentation: Help companies intelligently test and optimize customer messaging strategies
• Predictive Audiences: Build models to identify users most likely to convert, churn, or take key actions
• Content Generation: Leverage LLMs to generate compelling text, images, and creatives for marketing use
• Budget Optimization: Pinpoint where marketing spend delivers the best ROI and lowest marginal CAC

As a Founding ML Engineer, You Will:

• Work across customer discovery, problem definition, modeling, infrastructure, and customer-facing solutions
• Build core machine learning systems from the ground up
• Partner with cross-functional stakeholders and directly with customers
• Own end-to-end delivery of highly impactful intelligence features

About You

• You are curious, driven, and excited to solve hard, impactful technical problems
• You bring experience in building ML models and infrastructure OR have strong fundamentals and are eager to learn quickly
• You’re comfortable navigating ambiguity and working in a fast-paced, high-autonomy environment

Compensation

• Salary: $200,000–$260,000 USD
• Meaningful equity
• Fully remote, location-independent role

Interview Process

• Intro Call (15–30 min): Conversation with recruiting or hiring manager to explore mutual fit
• System Design Screen (45 min): Walkthrough of building a data processing feature end-to-end
• ML Modeling Interview (90 min): Design a predictive model including data prep, training, evaluation, and deployment
• System Design Interview (90 min): Architect a conceptual system given technical and customer/product requirements
• Hiring Manager Interview (30 min): Deep dive into past experiences, working style, and values alignment

No live coding interviews are included—emphasis is placed on product thinking, systems architecture, and company alignment.