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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
As a Machine Learning Engineer II, you will contribute to building and improving machine learning models and infrastructure that power real-time personalization across the Attentive platform. This role is ideal for an engineer who has solid production ML experience and is looking to grow their impact, technical depth, and ownership within a collaborative team environment.
You will work closely with senior ML engineers, product managers, and platform teams to implement end-to-end ML use cases while continuing to develop strong ML engineering fundamentals.
What You’ll Accomplish
- Build and maintain machine learning models and pipelines used in production
- Contribute to data processing, feature engineering, model training, and evaluation workflows
- Assist in deploying, monitoring, and validating ML models in production environments
- Partner with senior engineers and product managers to implement ML-driven features
- Write high-quality, well-tested code and help prevent regressions through testing and monitoring
- Learn and apply best practices in ML engineering, system reliability, and scalability
- Participate in design discussions, code reviews, and team knowledge sharing
- Grow your technical skills in a fast-paced, high-impact environment
Your Expertise
- 3+ years of professional software engineering experience, with 2+ years working on machine learning or data-driven systems
- Proficiency in Python and familiarity with ML frameworks such as PyTorch, TensorFlow, or xgboost
- Experience with data analysis and processing tools such as pandas, SQL, Spark, or similar
- Exposure to building or supporting ML pipelines for training, validation, or deployment
- Understanding of production concerns such as monitoring, performance, and data quality
- Strong collaboration and communication skills, with a growth-oriented mindset
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 $212,000 - 280,000 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
