Senior Machine Learning Engineer
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.
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
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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