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AttentiveAttentiveNew York, NY

Staff Software Engineer, Machine Learning

Builds, scales, and operates production-grade ML systems for real-time personalization on Attentive's platform. Requires 6+ years experience with Python, PyTorch/TensorFlow, and scalable ML pipelines in a fast-paced environment.

320k – 360k/yr
Remote6+ YOEML Engineering

About the role

What You’ll Accomplish

  • You have a proven track record of building systems that maintain a high bar of quality
  • You deeply loathe regressions and take proactive steps to protect against them through a variety of testing techniques
  • You are a collaborator, technical leader, and a great communicator
  • 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
  • You are enthusiastic about the high impact, fast-paced work environment of an late-stage startup
  • 10+ years experience is ideal

Your Expertise

  • You have worked professionally building systems for 6+ years with experience on a single system long enough to see the consequences of your decisions
  • Experience with TensorFlow/PyTorch, xgboost, pandas, matplotlib, SQL, Spark or similar tools
  • You have proficiency or experience with Python
  • 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

What We Use

  • Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS
  • Infrastructure tooling includes Istio, Datadog, Terraform, CloudFlare, and Helm
  • Our backend is Java / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, Kinesis, AirFlow, Postgres, Planetscale, and Redis, hosted via AWS
  • 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, lots of data and built with Python, Metaflow, HuggingFace, PyTorch, TensorFlow, and Pandas

Compensation

For US based applicants: The US base salary range for this full-time position is $320,000 - $360,000 annually + equity + benefits

Skills

PythonPyTorchTensorFlowXgboostpandasKubernetesAWSSparkSQLHuggingfaceMetaflow

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