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6 часов назад

AI Applications Engineer (LLM)

100 000 - 175 000$
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

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TL;DR
AI Applications Engineer (LLM): Designing and operationalizing fine-tuning workflows for large language models across supervised, preference-based, and reinforcement learning approaches with an accent on dataset construction, evaluation methodology, and production-grade training pipelines. Focus on distributed training, GPU cluster reliability, preference optimization, and shipping impactful LLM systems.

Location: 100% remote within the United States

Salary: $100,000–$175,000 annually

Company

hirify.global is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States.

What you will do

  • Design, execute, and operationalize fine-tuning workflows for large language models using supervised, preference-based, and reinforcement learning approaches.
  • Construct high-quality datasets and develop rigorous benchmark and human evaluation methodologies.
  • Operate large-scale training jobs on GPU clusters and recover reliably from failures.
  • Navigate trade-offs between data quality, compute budget, evaluation rigor, and delivery speed.
  • Translate ambiguous requirements into production-grade solutions with product, design, engineering, operations, and business stakeholders.
  • Contribute through code reviews, design reviews, and mentorship of junior engineers.

Requirements

  • Master’s or PhD in Computer Science, Machine Learning, or a related field, or equivalent experience.
  • 6+ years of combined ML research and engineering experience with significant LLM exposure.
  • Strong proficiency in Python, PyTorch, and modern deep learning frameworks.
  • Hands-on experience fine-tuning transformer-based language models at non-trivial scale.
  • Experience with distributed training strategies including FSDP, ZeRO, and pipeline parallelism.
  • Experience with RLHF, DPO, preference optimization, GPU cluster operations, and LLM work shipped or published with meaningful impact.

Nice to have

  • Publications at top-tier ML venues.
  • Experience with multimodal model fine-tuning, synthetic data generation, or dataset distillation.
  • Open-source contributions to LLM training libraries.
  • Exposure to responsible AI evaluation and red-teaming practices.

Culture & Benefits

  • Full-time direct W2 employment.
  • Remote work within the United States.
  • Career growth opportunities within an established technology organization.
  • New H-1B visa petitions are not sponsored; U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply.

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