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
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
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