Machine Learning Engineer, AI Decisioning

Machine Learning Engineer, AI Decisioning (Full-time)

Location : Remote (North America) / San Francisco (Optional)

Salary Range : $200,000 - $260,000 USD

We are expanding our data activation products to include a powerful intelligence layer, and we are looking for a highly experienced Machine Learning Engineer to join our team. Hundreds of companies use our platform to automate and improve operations by syncing data into their systems, but there is immense potential in helping them make smarter decisions about which customers to message, what content to use, and when to send messages.

A lot of this crucial decision-making today is often manual and driven by intuition. By integrating machine learning, we aim to deliver a step-function impact for our customers. Given our access to first-party customer data, we are perfectly positioned to build an intelligence layer that leverages this rich data source.

Your responsibilities will include working on complex problems such as :

• Personalization and Product Recommendation : Designing and implementing models to personalize messages and content (including product catalogs) to ensure the most relevant content is delivered to each individual user.
• Automated Experimentation : Developing intelligent systems to help customers efficiently navigate and automate A / B testing and experimentation across a vast number of messaging options.
• Predictive Audiences : Building robust models to predict customer actions, such as conversion, churn, or other desired behaviors, to create targeted audiences.
• Content Generation : Leveraging recent advancements in Large Language Models (LLMs) to help marketers generate compelling text, images, and creative assets.
• Budget Optimization : Creating analytical tools and models to assess which marketing spend drives the most incremental conversions and identifies where the marginal Customer Acquisition Cost (CAC) is lowest.
• Experience : 5 - 15 years of professional experience in machine learning and software development.
• Domain Expertise : Deep understanding and practical experience building and deploying machine learning models, particularly in areas like personalization, recommendation systems, time-series analysis, or optimization.
• Technical Skills : Strong software engineering fundamentals and experience working with large-scale data warehouses / databases.
• Communication : Excellent communication skills with the ability to articulate complex technical concepts to both technical and non-technical stakeholders.
• Mindset : A strong first-principles thinking approach to problem-solving, a growth mindset, and a motivated, persistent approach to achieving goals.
• Competitive Compensation : Highly competitive salary in the range of $200K - $260K USD .
• Equity : Competitive equity package in a high-growth company with a recent $1.2B valuation, backed by leading investors.
• Visa Sponsorship : Visa sponsorship is available for qualified candidates.
• Work Flexibility : Full-time, remote position supporting work across North America .
• Impact : The opportunity to make a meaningful impact by defining the future of AI-powered customer data activation.

Due to the high volume of applications we anticipate, we regret that we are unable to provide individual feedback to all candidates. If you do not hear back from us within 4 weeks of your application, please assume that you have not been successful on this occasion. We genuinely appreciate your interest and wish you the best in your job search.

Commitment to Equality and Accessibility :

At MLabs, we are committed to offer equal opportunities to all candidates. We ensure no discrimination, accessible job adverts, and providing information in accessible formats. Our goal is to foster a diverse, inclusive workplace with equal opportunities for all. If you need any reasonable adjustments during any part of the hiring process or you would like to see the job-advert in an accessible format please let us know at the earliest opportunity by emailing human-resources@mlabs.city.

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