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AI Engineer

Summary by AIEngineer.careers

AI Engineer is a AI Engineer role (part-time). with DE Shaw. in DENVER, US. Compensation shown: $115K–$166K. Imported listing (source: macdailyguide.com). Apply on the employer's site (macdailyguide.com).

Imported listing (source: macdailyguide.com) · Apply on macdailyguide.com

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DENVER · US
$115K–$166K
Part-time
SENIOR
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The sections below reproduce the third-party job description for reference. AIEngineer.careers does not write or control this text.

Imported job description

Sourced from macdailyguide.com

DE Shaw is hiring a Senior AI Engineer in Denver, CO to build and scale deep learning services and Azure ML workflows. The role blends hands-on model engineering with statistical rigor, owning a hypothesis testing subsystem and driving engineering excellence across the team.

Responsibilities

  • Manage Hypothesis Testing configuration across environments so staging mirrors production
  • Apply Azure ML and Hypothesis Testing to solve engineering challenges
  • Own the impact-driven Hypothesis Testing subsystem
  • Scale Deep Learning services from pilot to statewide rollout
  • Champion engineering excellence and continuous learning

Requirements

  • Hands-on command of Keras and Hypothesis Testing
  • Proven Azure ML experience
  • Demonstrated Deep Learning expertise in a fast-moving environment
  • Experience translating Looker complexity for non-technical audiences
  • Strong ownership mindset
  • Willingness to relocate to Denver, CO or work remotely

Nice to Have

  • Regression Analysis
  • Computer Vision
  • Feature Engineering
  • Statistical Modeling
  • Initiative
  • Communication
  • Prioritization

Benefits

Health insurancecoachingflexible schedule

Tech Stack

Azure MLComputer VisionDeep LearningFeature EngineeringHypothesis TestingKerasLookerRegression AnalysisStatistical Modeling
DS

DE Shaw

New York · US · 3000+ employees

The D. E. Shaw Group is a global investment and technology-development firm founded in 1988. It combines systematic and fundamental investment approaches with quantitative tools, human-driven insights, and proprietary technology across public and private markets.

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