VP of AI Engineering

crossing hurdles United State
Remote
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AI Summary

Lead AI engineering across core products and research tooling. Establish best practices for model evaluation, human-in-the-loop data, and feedback systems. Contribute hands-on to model development and backend systems as needed.

Key Highlights
Lead AI engineering team
Establish best practices for model evaluation
Contribute hands-on to model development
Key Responsibilities
Own and lead AI engineering across core products and research tooling
Evaluate, fine-tune, and build on top of foundation models
Establish best practices for model evaluation, human-in-the-loop data, and feedback systems
Lead, scale, and mentor a globally distributed AI engineering team
Contribute hands-on to model development and backend systems as needed
Technical Skills Required
AI/ML systems Large language models Model evaluation frameworks Human-in-the-loop systems Data quality
Benefits & Perks
$1.5M–$2M/year
Remote work
10–40 hours/week

Job Description


Position: VP of AI Engineering

Type: Full-time

Compensation: $1.5M–$2M/year

Location: Remote

Commitment: 10–40 hours/week


Role Responsibilities

  • Own and lead AI engineering across core products and research tooling.
  • Evaluate, fine-tune, and build on top of foundation models; train non-LLM models where required.
  • Establish best practices for model evaluation, human-in-the-loop data, and feedback systems.
  • Lead, scale, and mentor a globally distributed AI engineering team.
  • Contribute hands-on to model development and backend systems as needed.
  • Set technical direction for new AI tools and platforms in close collaboration with Product and Engineering.
  • Partner directly with the CEO on technical strategy, hiring, and execution.
  • Support customer-facing technical discussions when required.


Requirements

  • Deep, hands-on experience building and deploying AI/ML systems in production environments.
  • Strong background in training models from scratch and fine-tuning large language models.
  • Advanced understanding of evaluation frameworks, human-in-the-loop systems, and data quality.
  • Proven technical leadership with a strong execution-oriented mindset.
  • Ability to operate effectively in fast-paced, ambiguous environments.
  • Excellent communication skills across technical and non-technical stakeholders.


Application Process (Takes 20 Min)

  • Upload resume
  • Interview
  • Submit form

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