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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. 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
#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.
Attentive New York, New York, USA Office
136 Madison Avenue, New York, NY, United States, 10016
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory



