6 часов назад
AI Applications Engineer (LLM)
100 000 - 175 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
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
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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