6+ years of experience building production machine learning systems
Experience managing ML systems with visible downstream impacts
Strong proficiency in Python and familiarity with ML frameworks like PyTorch and TensorFlow
Skilled in data processing tools such as pandas, SQL, and Spark
Hands-on experience with automated pipelines for ML model training and deployment
Collaborative mindset for working with cross-functional teams
Strong communication skills and a high degree of ownership.
Responsibilities
Design and operate scalable machine learning systems for real-time personalization
Manage ML projects from data exploration to deployment and monitoring
Ensure model quality through rigorous testing and validation processes
Collaborate with teams to convert business challenges into ML solutions
Enhance system reliability and engineering efficiency continuously
Provide technical guidance and best practices to the ML engineering team
Mentor fellow engineers through design discussions and code reviews.
Benefits
Diverse benefits focusing on health and wellness
Equity opportunities for employees
Flexible working arrangements with a global team
Support for personal growth and continuous learning
Inclusive workplace culture with diversity initiatives.
Full Job Description
About the RoleOur 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
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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About Attentive
Attentive is a mobile marketing company that provides a platform for businesses to communicate with their customers via text messaging. The platform includes features such as personalized messaging, automation, and analytics. Attentive's platform is used by businesses to increase customer engagement, drive sales, and improve customer experience. The company was founded in 2016 and is headquartered in New York, New York.
