Staff Software Engineer, Machine Learning

Attentive Attentive · Enterprise · United States · Engineering

Staff Software Engineer, Machine Learning at Attentive, an AI marketing platform focused on 1:1 personalization. The role involves building, scaling, and operating production-grade ML systems for real-time personalization, requiring strong experience in ML systems development, data analysis, and cross-functional project leadership within a fast-paced, late-stage startup environment.

What you'd actually do

  1. You have a proven track record of building systems that maintain a high bar of quality
  2. You deeply loathe regressions and take proactive steps to protect against them through a variety of testing techniques
  3. You are a collaborator, technical leader, and a great communicator
  4. You are constantly improving the quality of the project you are working on, both via direct contributions as well as long-term advocacy for larger-scale changes
  5. You are enthusiastic about the high impact, fast-paced work environment of an late-stage startup

Skills

Required

  • Python
  • TensorFlow/Pytorch
  • xgboost
  • pandas
  • matplotlib
  • SQL
  • Spark
  • machine learning
  • data analysis
  • scalable systems
  • data-driven products
  • automated processes
  • model development
  • model validation
  • model implementation
  • cross-functional machine learning projects

Nice to have

  • Kubernetes
  • AWS EKS
  • Istio
  • Datadog
  • Terraform
  • CloudFlare
  • Helm
  • Java
  • Spring Boot
  • DynamoDB
  • Kinesis
  • AirFlow
  • Postgres
  • Planetscale
  • Redis
  • React
  • TypeScript
  • GraphQL
  • Storybook
  • Radix UI
  • Vite
  • esbuild
  • Playwright
  • Metaflow
  • HuggingFace
  • PyTorch
  • TensorFlow
  • Pandas

What the JD emphasized

  • 10+ years experience is ideal
  • You have worked professionally building systems for 6+ years with experience on a single system long enough to see the consequences of your decisions
  • You have extensive experience using machine learning and data analysis, or similar, to build scalable systems and data-driven products, working with cross-functional teams
  • You have a proven track record of building scalable, efficient, automated processes for large-scale data analyses, model development, model validation, and model implementation from modern research
  • You have led cross-functional machine learning projects across teams

Other signals

  • production-grade ML systems
  • real-time personalization
  • scaling and operating ML systems
  • late-stage startup