Staff Machine Learning Engineer

Attentive® is the AI-powered mobile marketing platform transforming the way brands personalize consumer engagement. Attentive enables marketers to craft tailored journeys for every subscriber, driving higher recurring revenue and maximizing campaign performance. Activating real-time data from multiple channels and advanced AI, the platform personalizes content, tone, and timing to deliver 1:1 messages that truly resonate.

With a top-rated customer success team recognized on G2, Attentive partners with marketers to provide strategic guidance and optimize SMS and email campaigns. Trusted by leading global brands like Neiman Marcus, Samsung, Wayfair, and Dyson, Attentive ensures enterprise-grade compliance and deliverability, supporting trillions of interactions across more than 70 industries. To learn more or request a demo, visit www.attentive.com or follow us on LinkedIn, X (formerly Twitter), or Instagram.

Attentive's growth has been recognized by Deloitte's Fast 500, Linkedin's Top Startups and Forbes Cloud 100 all thanks to the hard work from our global employees!

About the Attentive Team

Have you ever received text message marketing from your favorite brand with an incredible offer? Did you know that effective text message marketing is by far the highest ROI marketing channel? And did you know that customers are increasingly preferring to interact with brands through text? That is what we do at Attentive. We help the world's largest brands interact with their clients at the right time and with the right message. Our platform powers more than 400 million messages per day, approaching 100 billion per year.

We're building big things! Check out our tech blog here: https://tech.attentive.com/

About the Role

Our Machine Learning Engineering team powers personalized experiences for hundreds of millions of customers across thousands of brands. We build advanced ML models that predict customer behaviors in real-time, enabling highly personalized shopping experiences. Joining our team offers a high-growth career opportunity to work with some of the world's most talented machine learning engineers in a high-performance and high-impact culture.

We are seeking a self-driven and highly motivated Machine Learning Engineer to join our growing machine learning teams. As an early hire, you will contribute to the development of machine learning models and infrastructure needs across the Attentive platform and work with Product Management and Engineering to implement end-to-end modeling use cases.

What You'll Accomplish

• You have a proven track record of building systems that maintain a high bar of quality
• You deeply loathe regressions and take proactive steps to protect against them through a variety of testing techniques
• You are a collaborator, technical leader, and a great communicator
• You are constantly improving the quality of the project you are working on, both via direct contributions as well as long-term advocacy for larger-scale changes
• You are enthusiastic about the high impact, fast-paced work environment of an late-stage startup
• 10+ years experience is ideal

Your Expertise

• You have worked professionally building systems for 6+ years with experience on a single system long enough to see the consequences of your decisions
• Experience with TensorFlow/Pytorch, xgboost, pandas, matplotlib, SQL, Spark or similar tools
• You have proficiency or experience with Python
• You have extensive experience using machine learning and data analysis, or similar, to build scalable systems and data-driven products, working with cross-functional teams
• You have a proven track record of building scalable, efficient, automated processes for large-scale data analyses, model development, model validation, and model implementation from modern research
• You have led cross-functional machine learning projects across teams

What We Use

• Our infrastructure runs primarily in Kubernetes hosted in AWS's EKS
• Infrastructure tooling includes Istio, Datadog, Terraform, CloudFlare, and Helm
• Our backend is Java / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, Kinesis, AirFlow, Postgres, Planetscale, and Redis, hosted via AWS
• Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and Playwright
• Our automation is driven by custom and open source machine learning models, lots of data and built with Python, Metaflow, HuggingFace 🤗, PyTorch, TensorFlow, and Pandas