Senior Machine Learning Engineer
AttentiveSan Francisco, CA$244k – $320kPosted 7 April 2026
Tech Stack
Job Description
Attentive® is the AI marketing platform for 1:1 personalization redefining the way brands and people connect. We’re the only marketing platform that combines powerful technology with human expertise to build authentic customer relationships. By unifying SMS, RCS, email, and push notifications, our AI-powered personalization engine delivers bespoke experiences that drive performance, revenue, and loyalty through real-time behavioral insights.
Recognized as the #1 provider in SMS Marketing by G2, Attentive partners with more than 8,000 customers across 70+ industries. Leading global brands like Crate and Barrel, Urban Outfitters, and Carter’s work with us to enable billions of interactions that power tens of billions in revenue for our customers.
With a distributed global workforce and employee hubs in New York City, San Francisco, London, and Sydney, Attentive’s team has been consistently recognized for its performance and culture. We’re proud to be included in Deloitte’s Fast 500 (four years running!), LinkedIn’s Top Startups , Forbes’ Cloud 100 (five years running!), Inc.’s Best Workplaces , and the Human Rights Campaign Foundation's Corporate Equality Index !
About the Role
Our Machine Learning Engineering team powers personalized experiences for hundreds of millions of customers across thousands of brands. As a Senior Machine Learning Engineer, you will play a critical role in building, scaling, and operating production-grade ML systems that drive real-time personalization across the Attentive platform.
You will operate with a high degree of ownership, partner closely with Product and Engineering, and help raise the technical bar across our ML systems in a fast-paced, high-impact environment.
What You’ll Accomplish
Design, build, and operate scalable machine learning systems used in real-time targeting, decisioning, personalization systems
Own ML projects end-to-end, from data exploration and modeling to deployment, monitoring, and iteration
Proactively safeguard model and system quality through testing, monitoring, validation, and alerting
Collaborate cross-functionally with product, data, and other engineering partners to translate business problems into ML solutions
Continuously improve system reliability, performance, and engineering efficiency
Contribute to technical direction and best practices across the ML engineering team
Mentor and support other engineers through code reviews, design discussions, and knowledge sharing
Thrive in a high-impact, fast-paced, late-stage startup environment
Your Expertise
6+ years of professional experience building production machine-learning software systems
Proven experience owning ML systems long enough to see the downstream impact of design decisions
Strong proficiency in Python and experience with ML frameworks such as PyTorch, TensorFlow, or xgboost
Experience with data processing and analytics tools such as pandas, Spark, SQL, and matplotlib
Hands-on experience building automated pipelines for data processing, model training, validation, and deployment
Experience collaborating with cross-functional teams to deliver ML-powered features
Strong communication skills and a high sense of ownership
What We Use
Infrastructure: Kubernetes (AWS EKS), Istio, Datadog, Terraform, Cloudflare, Helm
Backend: Java / Spring Boot microservices (Gradle), DynamoDB, Kinesis, Airflow, Postgres, PlanetScale, Redis
Frontend: React, TypeScript, GraphQL, Storybook, Radix UI, Vite, Playwright
ML Data: Python, Metaflow, HuggingFace 🤗, PyTorch, TensorFlow, Panda
You'll get competitive perks and benefits , from health wellness to equity, to help you bring your best self to work.
For US based applicants:
The US base salary range for this full-time position is $244,000 - 320,000 annually + equity + benefits
Our salary ranges are determined by role, level and location
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