Senior ML Engineer — Real-Time Personalization Platform

Attentive

New York (NY)

On-site

USD 320,000 - 360,000

Full time

14 days+

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Benefits offered by this job

Health & wellness
Equity

Job summary

Attentive is seeking a Senior Machine Learning Engineer to build, scale, and operate production-grade ML systems that power real-time personalization across the Attentive platform. You will own major components, collaborate with product and engineering, and raise the technical bar in a fast-paced, late-stage startup environment.

We value ownership, communication, and a track record of delivering scalable ML solutions with cross-functional teams, TensorFlow/PyTorch, and Python.

Qualifications

  • 6+ years developing large-scale ML systems.
  • 0
  • Experience with end-to-end ML projects from data collection to deployment.
  • 0
  • Strong Python and ML tooling skills.
  • 0
  • Ability to work with cross-functional teams.
  • 0
  • Proven track record of reducing regressions.

Responsibilities

  • Build and scale production-grade ML systems.
  • 0
  • Partner with product and engineering to raise the technical bar.
  • 0
  • Own testing strategies to prevent regressions.
  • 0
  • Lead cross-functional ML projects.
  • 0
  • Collaborate on data-driven product improvements.
  • 0
  • Operate in a fast-paced late-stage startup environment.

Skills

TensorFlow/PyTorch
xgboost
pandas
matplotlib
SQL
Spark
Python
ML systems
data analysis
cross-functional leadership
project leadership

Tools

AWS
Kubernetes
DynamoDB
Kinesis
Postgres
Planetscale
Redis
AirFlow
Datadog

Job description

Attentive is seeking a Senior Machine Learning Engineer to build, scale, and operate production-grade ML systems that power real-time personalization across the Attentive platform. You will own major components, collaborate with product and engineering, and raise the technical bar in a fast-paced, late-stage startup environment.

We value ownership, communication, and a track record of delivering scalable ML solutions with cross-functional teams, TensorFlow/PyTorch, and Python.

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