Why this role stands out
You can significantly impact the future of AI-powered personalization by developing cutting-edge machine learning models at Attentive, a recognized leader in marketing technology. This role offers exceptional growth potential and a competitive compensation package, ideal for experienced ML engineers passionate about building innovative solutions and driving measurable results.
Quick overview
Job description
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.
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
- Our backend is Java / Kotlin / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, Aurora, AirFlow, Postgres, and Redis, hosted via AWS
- Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS, using tooling like Istio, Datadog, Terraform, CloudFlare, and Helm
- Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and Playwright
- Our automation is driven by custom and open source machine learning models, industry-leading LLMs, lots of data and tech like Python, Metaflow, HuggingFace, PyTorch, TensorFlow, and Pandas
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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