Head of ML & Data Intelligence for Manufacturing

Hadrian Automation

Los Angeles (CA)

On-site

USD 249,000 - 299,000

Full time

14 days+
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Benefits offered by this job

Medical insurance
Dental insurance
Vision insurance
Life insurance
401k
Relocation support
Flexible vacation
Equity

Job summary

Hadrian Automation seeks an experienced engineering leader for the Technical Data Intelligence team. You will guide a world-class group focused on making engineering data actionable for automation across ML and traditional software engineering.

The role combines hiring, mentorship, and strategic input with hands-on participation in design and implementation to accelerate impact. You will mentor engineers, shape architecture, and drive initiatives like data annotation tooling, active learning,

Qualifications

  • 2-5+ years of engineering management experience leading ML engineering teams in production.
  • Strong depth in ML, computer vision (detection/segmentation), multimodal image+text models, and/or data engineering.

Responsibilities

  • Own people leadership: hiring, onboarding, mentorship, career growth, performance.
  • Stay hands-on as player-coach in design reviews and key work to unblock paths.
  • Set technical direction and headcount investments with engineers and leads.
  • Build/maintain annotation tooling, active learning loops, synthetic data augmentation strategies.
  • Ensure engineers are engaged, growing, and set up to do their best work.

Skills

ML engineering leadership
Machine learning
Computer vision
Data engineering
Team building & mentorship

Job description

Hadrian Automation seeks an experienced engineering leader for the Technical Data Intelligence team. You will guide a world-class group focused on making engineering data actionable for automation across ML and traditional software engineering.

The role combines hiring, mentorship, and strategic input with hands-on participation in design and implementation to accelerate impact. You will mentor engineers, shape architecture, and drive initiatives like data annotation tooling, active learning,

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