The Staff Machine Learning Engineer will develop ML models and infrastructure for personalized experiences, collaborating with teams to implement end-to-end solutions and ensure high quality in systems development.
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!), and Inc.’s Best Workplaces.
About the Role
Our Machine Learning Engineering team powers personalized experiences for hundreds of millions of customers across thousands of brands. We build advanced ML models that predict customer behaviors in real-time, enabling highly personalized shopping experiences. Joining our team offers a high-growth career opportunity to work with some of the world’s most talented machine learning engineers in a high-performance and high-impact culture.
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.
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 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
- 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 $288,000 - $330,000 annually + equity + benefits
- Equity is a substantial part of the total compensation package
- Our salary ranges are determined by role, level and location
#LI-EF1
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.
Top Skills
Airflow
AWS
Cloudflare
Datadog
DynamoDB
Esbuild
Gradle
GraphQL
Helm
Huggingface
Istio
Java
Kinesis
Kubernetes
Matplotlib
Metaflow
Pandas
Planetscale
Playwright
Postgres
Python
PyTorch
Radix Ui
React
Redis
Spark
Spring Boot
SQL
Storybook
TensorFlow
Terraform
Typescript
Vite
Xgboost
Similar Jobs
Blockchain • eCommerce • Fintech • Payments • Software • Financial Services • Cryptocurrency
As a Staff/Principal Machine Learning Engineer, you'll build and maintain ML models for credit products, design decision frameworks, and run experiments to ensure model performance. You'll work across the full modeling lifecycle and collaborate with various teams to align credit risk assessments with business goals.
Top Skills:
AWSClaude CodeCopilotCursorGCPGitLightgbmMlflowNumpyPandasPythonPyTorchScikit-LearnSnowflakeSQLXgboost
Blockchain • Fintech • Mobile • Payments • Software • Financial Services
The role involves building and evolving machine learning systems for credit decisioning, managing the full modeling lifecycle, and collaborating cross-functionally to ensure regulatory compliance and business goals are met.
Top Skills:
AWSClaude CodeCopilotCursorGCPGitLightgbmMlflowNumpyPandasPythonPyTorchScikit-LearnSnowflakeSQLXgboost
Blockchain • eCommerce • Fintech • Payments • Software • Financial Services • Cryptocurrency
The Staff Machine Learning Engineer will lead Bitcoin risk modeling efforts, drive ML strategy, develop detection models, and mentor teammates.
Top Skills:
AirflowAWSGCPMlflowModeMySQLNumpyPandasPrefectPysparkPythonPyTorchScikit-LearnSnowflakeTableauTensorflow/KerasXgboost
What you need to know about the Los Angeles Tech Scene
Los Angeles is a global leader in entertainment, so it’s no surprise that many of the biggest players in streaming, digital media and game development call the city home. But the city boasts plenty of non-entertainment innovation as well, with tech companies spanning verticals like AI, fintech, e-commerce and biotech. With major universities like Caltech, UCLA, USC and the nearby UC Irvine, the city has a steady supply of top-flight tech and engineering talent — not counting the graduates flocking to Los Angeles from across the world to enjoy its beaches, culture and year-round temperate climate.
Key Facts About Los Angeles Tech
- Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Snap, Netflix, SpaceX, Disney, Google
- Key Industries: Artificial intelligence, adtech, media, software, game development
- Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
- Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering
