Principal Software Engineer, Machine Learning
San Francisco, CA (Hybrid)
- Pay
$350,000–430,000/year · Base — pay source
For US based applicants: The US base salary range for this full-time position is $350,000 - $430,000 annually + equity + benefits Our salary ranges are determined by role, level and location
Read the full posting- Work setting
Hybrid — work setting source
Listed location: San Francisco, CA (Hybrid)
Read the full posting- Employment
Full-time — employment source
Employment type in the employer’s posting: Full Time
From the employer’s posting
What you’ll work on
Full postingBuild and scale production-grade ML systems for real-time personalization
Lead cross-functional machine learning projects across teams
Partner with Product and Engineering with a high degree of ownership
Raise quality and reduce regressions through testing and long-term advocacy
From the employer’s posting
building, scaling, and operating production-grade ML systems that drive real-time personalization
You have led cross-functional machine learning projects across teams
partner closely with Product and Engineering
You deeply loathe regressions and take proactive steps to protect against them through a variety of testing techniques
What you’ll bring
All qualificationsCore experience
- 10+ years building production systems, ideally with one system long-term
- Experience with TensorFlow/PyTorch, XGBoost, pandas, SQL, Spark or similar
- Proficiency or experience with Python
- Experience building scalable data-driven products with ML and data analysis
Qualification wording
You have worked professionally building systems for 10+ years
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
Tools in this posting
- Java
- Python
- SQL
- TypeScript
- AWS
- Datadog
- DynamoDB
- Kubernetes
- Redis
- Spark
- Terraform
- Airflow
- Hugging Face
- Matplotlib
- pandas
- PyTorch
- React
- TensorFlow
- XGBoost
- PostgreSQL
Source — Tool mentions in context
- 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
- 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
- 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 You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.
- You have worked professionally building systems for 10+ 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
- 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
What We Use - Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS - Infrastructure tooling includes Istio, Datadog, Terraform, CloudFlare, and Helm
- 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
Posting record
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- Live
- First seen by us
- Sep 21, 2026 · 38 days ago
- Recorded sightings
- 38
- Last seen by us
- Oct 29, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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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!
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
- 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 10+ 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
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 $350,000 - $430,000 annually + equity + benefits
- Our salary ranges are determined by role, level and location
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Attentive Company Values
Default to Action - Move swiftly and with purpose
Be One Unstoppable Team - Rally as each other’s champions
Champion the Customer - Our success is defined by our customers' success
Act Like an Owner - Take responsibility for Attentive’s success
Learn more about AWAKE, Attentive’s collective of employee resource groups.
If you do not meet all the requirements listed here, we still encourage you to apply! No job description is perfect, and we may also have another opportunity that closely matches your skills and experience.
At Attentive, we know that our Company's strength lies in the diversity of our employees. Attentive is an Equal Opportunity Employer and we welcome applicants from all backgrounds. Our policy is to provide equal employment opportunities for all employees, applicants and covered individuals regardless of protected characteristics. We prioritize and maintain a fair, inclusive and equitable workplace free from discrimination, harassment, and retaliation. Attentive is also committed to providing reasonable accommodations for candidates with disabilities. If you need any assistance or reasonable accommodations, please let your recruiter know.
Source details
Source notes
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- Pay
For US based applicants: The US base salary range for this full-time position is $350,000 - $430,000 annually + equity + benefits Our salary ranges are determined by role, level and location
- Location & working pattern
San Francisco, CA (Hybrid)
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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