Job Description

Machine Learning Engineer, AI Decisioning

Remote – North America

Salary: $200,000 – $260,000 USD

Academic excellence - Coming from top 50 CS or EE schools and degrees.

About the Company

This fast-growing, remote-first tech company is on a mission to empower teams across industries to take action on their data. With a customer base that includes global names in e-commerce, SaaS, and retail, their platform enables organisations to collect, prepare, and activate customer data from their data warehouses to power personalised experiences and business operations.

The company recently introduced an AI Decisioning platform that helps marketers move beyond manual processes by leveraging AI to drive 1:1 personalisation. The platform allows business users—not just technical teams—to deliver impactful, data-driven customer interactions by setting goals and guardrails for AI agents.

With a supportive, impact-driven culture, the team is known for its fast execution, thoughtful collaboration, and strong values. The company has global team members, a strong funding history including a recent Series C that brought them to unicorn status, and backing from top-tier investors in the tech ecosystem.

The Role

As a Machine Learning Engineer, you'll be part of a new initiative focused on embedding intelligence directly into the platform’s data activation products. The team is building a foundational intelligence layer designed to guide companies on who to target, what content to serve, and when to engage, transforming guesswork into data-informed decision-making.

Key problem areas include:

• Personalisation & Recommendations : Tailoring messaging and product suggestions using customer data.
• Automated Experimentation : Powering smarter, scalable A/B and multivariate testing.
• Predictive Audiences : Identifying users likely to convert, churn, or engage.
• Content Generation : Leveraging LLMs to create compelling text, images, and creatives.
• Budget Optimisation : Determining how to allocate spend most effectively to maximise ROI.

As one of the early ML engineers, you’ll work across the stack—engaging in problem definition, modeling, infrastructure, and customer collaboration. This is a senior-level role with a focus on impact and growth potential, not just years of experience.

Ideal Background:

• Experience building and deploying machine learning systems in production.
• Strong understanding of personalisation, recommendation systems, predictive modelling, or experimentation frameworks.
• Familiarity with large language models and generative AI applications is a plus.
• Hands-on with modern data infrastructure and capable of working closely with customer or product data.
• Comfortable working in a fast-paced, remote-first environment where initiative and ownership are key.

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