Engineering Manager, Machine Learning - Attentive

Job Title: Engineering Manager, Machine Learning
Job Location: San Francisco, CA
Job Listing URL: https://jobs.lever.co/attentive/f0efaf98-4fa7-4101-8b31-00052e9ed9ce
Job Description: 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 Role
Our Engineering team creates innovative product experiences that power personalized marketing at massive scale. We develop cutting-edge applications and systems that process hundreds of billions of messages and events per year, enabling marketers to connect effectively with hundreds of millions of consumers. Joining our team offers a high-growth career opportunity to work with some of the world’s most talented engineers in a high-performance and high-impact culture.

As an Engineering Manager in our Machine Learning org, you will lead a team of machine learning engineers in developing and enhancing our marketing platform by leveraging data, insights, and developing machine learning models. You will guide the technical direction of projects, foster a culture of collaboration, and ensure the successful delivery of high-quality software. This is a hands-on leadership role where you will balance people management, technical oversight, and cross-functional collaboration with product managers, data scientists, and other engineering teams.
What You'll Accomplish
Lead a team of machine learning engineers in designing, developing, and deploying scalable machine learning systems that power our AI-driven customer engagement products
Collaborate with product management to plan, define, and scope the end-to-end development of production models that align with business goals
Provide technical guidance and architectural direction, ensuring best practices in system design, data processing, and machine learning integration
Foster a strong engineering culture by mentoring and developing team members, driving continuous improvement in code quality, and advocating for best practices
Ensure the reliability, performance, and maintainability of our applications, enabling the delivery of billions of messages daily
Collaborate with other engineering leaders to shape the technical roadmap and improve our engineering processes
Your Expertise
7+ years of professional experience in machine learning, with at least 3 years in a leadership role with at least 4-8 reports
Experience leading teams that build and deploy machine learning-driven products
Strong proficiency in Python and requisite libraries (data analysis, plotting, modeling, etc.) including expertise in designing and maintaining scalable, high-performance machine learning systems
Excellent coaching, mentorship, and leadership skills, with a track record of growing and developing machine learning engineers
Ability to translate business needs into clearly scoped projects and technical solutions
Strong understanding of software engineering best practices, including code reviews, testing, CI/CD, and monitoring
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 PlaywrightOur automation is driven by custom and open source machine learning models, lots of data and built with Python, Metaflow, HuggingFace 🤗, PyTorch, TensorFlow, and Pandas