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Senior Software Engineer, ML Platform
AttentiveSan Francisco, United Statesfull_timeVerifiedPosted 4 Sept 2025
💰 $230,000/yr($170,000/yr – $230,000/yr)
About the role
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 RoleWe’re looking for a self-motivated, highly driven Senior Software Engineer to join our Machine Learning Platform (MLOps) team. As a team, we enable Attentive’s Machine Learning (ML) practice to directly impact Attentive’s AI product suite through the tools to train, inference, and deploy ML models with higher velocity and performance, while maintaining reliability. We build and maintain a foundational ML platform spanning the full ML lifecycle for consumption by ML engineers and data scientists. This is an exciting opportunity to join a rapidly growing ML Platform team at the ground floor with the ability to drive and influence the architectural roadmap enabling the entire ML organization at Attentive. This team and role is responsible for building and operating the ML data, tooling, serving, and inference layers of the ML platform. We are excited to bring on more engineers to continue expanding this stack.
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 RoleWe’re looking for a self-motivated, highly driven Senior Software Engineer to join our Machine Learning Platform (MLOps) team. As a team, we enable Attentive’s Machine Learning (ML) practice to directly impact Attentive’s AI product suite through the tools to train, inference, and deploy ML models with higher velocity and performance, while maintaining reliability. We build and maintain a foundational ML platform spanning the full ML lifecycle for consumption by ML engineers and data scientists. This is an exciting opportunity to join a rapidly growing ML Platform team at the ground floor with the ability to drive and influence the architectural roadmap enabling the entire ML organization at Attentive. This team and role is responsible for building and operating the ML data, tooling, serving, and inference layers of the ML platform. We are excited to bring on more engineers to continue expanding this stack.
What You'll Accoplish
- Expand, mature, and optimize our ML platform built around cutting edge tooling like Ray, MLFlow, Metaflow, Argo, and Spark to support traditional, deep learning, and reinforcement learning ML models
- Build and mature capabilities to support CPU / GPU clusters, model performance monitoring, drift detection, automated roll-outs, and improved developer experience
- Build, operate, and maintain a low-latency, high volume ML serving layer covering both online and batch inference use cases
- Orchestrate Kubernetes and ML training / inference infrastructure exposed as an ML platform
- Expose and manage environments, interfaces, and workflows to enable ML engineers to develop, build, and test ML models and services
Your Expertise
- You have been working in the areas of ML Platform / MLOps / Platform Engineering / DevOps / Infrastructure for 5+ years, and have an understanding of gold standard practices and best in class tooling for ML
- Your passion is exposing platform capabilities through interfaces that enable high performance ML practices, rather than designing ML experiments (this team does not directly develop ML models)
- You understand the key differences between online and offline ML inference and can voice the critical elements to be successful with each to meet business needs
- You understand the importance of CI/CD in building high-performing teams and have worked with tools like Jenkins, CircleCI, Argo Workflows, and ArgoCD
- You are passionate about observability and worked with tools such as Splunk, Nagios, Sensu, Datadog, New Relic
Sample Projects
- Design and implement an online inference pipeline with champion/challenger shadow model testing
- Scale real-time feature streaming use cases to handle low-latency, high-volume RL use cases
- Build a universal data access layer (DAL) and serving interface to expose predictions to different parts of Attentive’s products
- Mature platform interfaces toward full self-service for stakeholders
- Improve existing build and release pipelines for better reliability and
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