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1 день назад

Principal Applied AI Engineer

175 000 - 200 000$
Формат работы
remote (только USA)
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
Principal Applied AI Engineer (LLM/ML): Architecting practical AI solutions and reusable platforms, including a centralized LLM client, evaluation harness, AI gateway, and specialized machine learning models, with an accent on measurable quality, cost, and business value. Focus on choosing between frontier LLMs, bespoke ML models, and traditional NLP, building reusable engineering assets, and governing prompt engineering, data privacy, model safety, and MLOps.

Location: Remote - NOAM

Annual base salary: $175,000–$200,000, plus an annual target bonus and benefits.

Company

hirify.global creates products and services focused on delivering a high-quality customer experience.

What you will do

  • Act as the primary technical consultant for product and architecture leaders designing and implementing AI systems.
  • Define when to use frontier LLMs, bespoke machine learning models, or traditional NLP based on performance, cost, and speed.
  • Lead the development of specialized machine learning models for tasks where they are the best technical option.
  • Build and evolve a central LLM platform with a unified client for OpenAI, Anthropic, and open-source models.
  • Develop reusable libraries, tools, vetted prompts, internal skills, and an evaluation harness for prototyping, A/B testing, and quality measurement.
  • Own the AI gateway and provide leadership with reporting on AI value, ROI, total cost of ownership, and operational efficiency.

Requirements

  • Extensive hands-on experience with LLM systems, including prompt engineering, RAG, fine-tuning, and agentic workflows.
  • Deep experience with traditional machine learning, including classification, regression, and NLP.
  • Experience designing and maintaining reusable software components, libraries, and APIs used by engineering teams.
  • Ability to explain complex technical trade-offs to technical and non-technical stakeholders.
  • Experience measuring AI performance, quality, and cost and using data to guide decisions.
  • Expertise in prompt engineering, data privacy, model safety, and MLOps practices.

Culture & Benefits

  • Core values include Ownership, Energy, Speed & Agility, Service, and Being Human.
  • Benefits eligibility begins on day one and includes medical, dental, vision, 401(k), and 401(k) match.
  • Unlimited planned paid time off and global mental health support.
  • On-demand learning and development, quarterly paid volunteer days, and a company-wide mentor program.
  • Fast-paced, agile environment with opportunities for career development and internal promotion.

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