Senior 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 help brands 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 GUESS, Urban Outfitters, and Steve Madden, 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!

Who we are
Our engineering department consists of 200+ people across multiple teams, such as application development, infrastructure, data platform, machine learning, and security. We believe our company will win in the long run through product innovation. To get there, we obsess over iteratively delivering customer value through rapid prototyping and data-driven decision-making.

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.

Why Attentive needs you

• 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

About you

• 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

Our scale

• 8,000 brands powered by Attentive sent over 2.2 billion text messages over Cyber Week 2023 (Black Friday/Cyber Monday) representing a growth of 31% from 2022
• We sent 32 billion SMS messages in 2023, up 32% YoY. That's an average of 87 million per day
• Our production cluster contains over 18,000 containers which serve 200+ services
• Our streaming services process over 80 billion events per month

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