Senior Machine Learning Engineer

Attentive

. Design, build, and operate scalable machine learning systems for real-time targeting, decisioning, and personalization .

Posted 10/26/2026full-timeSan Francisco • California • United StatesSenior💰 $244,000 - $320,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and deploying scalable machine learning systems, with a strong focus on Python programming and proficiency in ML frameworks. Capable of leading projects end-to-end while ensuring system reliability and mentoring team members.

Highest-signal resume keywords

Machine Learning System DesignPython ProficiencyML Frameworks (PyTorch, TensorFlow, xgboost)Automated Data PipelinesCross-Functional Collaboration

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningPythonPyTorchTensorFlowXgboostPandasSparkSQLMatplotlibAutomated Pipelines

Soft Skills

Strong CommunicationHigh Sense of Ownership

Industry Keywords

Real-Time TargetingDecisioningPersonalizationModel ValidationSystem Monitoring

Tech Stack

Tools & technologies

PandasPythonPyTorchSparkSQLTensorflow

About the role

Key responsibilities & impact

Design, build, and operate scalable machine learning systems for real-time targeting, decisioning, and personalization
Own ML projects end-to-end, from data exploration and modeling through deployment, monitoring, and iteration
Safeguard model and system quality through testing, monitoring, validation, and alerting
Collaborate with product, data, and engineering partners to translate business problems into ML solutions
Improve system reliability, performance, and engineering efficiency
Contribute to technical direction and best practices across the ML engineering team
Mentor and support engineers through code reviews, design discussions, and knowledge sharing
Build production-grade ML systems powering personalized experiences on Attentive’s AI marketing platform

Requirements

What you’ll need

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
Experience with ML frameworks such as PyTorch, TensorFlow, or xgboost
Experience with 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

Benefits

Comp & perks

Equity
Health and wellness benefits
Competitive perks and benefits
Reasonable accommodations for candidates with disabilities