Machine Learning Engineer, AI Decisioning

About the Job

Join a small, high-caliber team building an AI decisioning platform that powers truly personalized, 1:1 customer experiences. In this role, you’ll design and deploy end-to-end machine learning systems that decide who to message, what to say, and when to say it.

This is a remote role across North America, working on complex distributed systems that operate at the scale of millions of users.

What’s in it for you?

• $200,000 – $260,000 base salary

• Competitive equity package

• Remote role across North America (U.S. & Canada)

• Visa sponsorship available

• Build a greenfield AI decisioning platform with massive, real-time customer datasets

• Work on high-impact problems: personalization, experimentation, budget optimization, and predictive audiences

• Join a small, senior engineering team with a very high talent bar

• Opportunity to scale ML products from 0→1 and 1→10 in a fast-growing environment backed by top-tier investors

What You’ll Be Doing:

• Design and implement production machine learning models for personalization, recommendation, and predictive audience targeting

• Architect and build distributed, backend systems that serve decisions to millions of users in real time

• Develop and iterate contextual bandit and experimentation frameworks to optimize content, channels, and timing

• Create systems for automated experimentation and budget optimization, focusing on incremental lift and marginal CAC

• Own ML solutions end-to-end: data pipelines, feature engineering, training, evaluation, deployment, and monitoring

• Partner closely with product and marketing teams to translate goals into measurable decision policies and experiments

• Evaluate and integrate LLM- and generative-based approaches for scalable content and creative generation

• Contribute to technical direction, code quality, and best practices for a small, high-impact ML engineering team

What You’ll Need:

• 5–15 years of experience across machine learning and software engineering

• Proven experience building ML or data products 0→1 and 1→10 in a large-scale SaaS environment

• Hands-on experience with recommendation, personalization, ads, search, or pricing systems in production

• Strong backend engineering skills, including building distributed systems and data/ML infrastructure

• Proficiency in at least one modern programming language (e.g., Python, Go, Java, or similar)

• Degree in Computer Science, Mathematics, Statistics, or a related field, or equivalent practical experience

• Structured, first-principles thinker with excellent communication skills and the ability to explain complex systems clearly

Ready to make an impact?

Make your mark building the AI decisioning engine that powers personalized customer experiences at scale.



👉 Please click “Apply for this Job”