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AI Research Scientist

Формат работы
hybrid
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
AI Research Scientist (Machine Learning): Designing, training, evaluating, and optimizing large language models, multimodal architectures, and on-device inference systems with an accent on model efficiency, privacy-preserving AI, and distributed processing. Focus on prototyping novel architectures and training methods, developing benchmarks and datasets, and integrating research findings into production systems.

Location: Austin, TX, United States; hybrid work arrangement.

Company

hirify.global is building a distributed AI infrastructure platform for private, scalable, personalized AI running on standard consumer hardware and at the edge.

What you will do

  • Design, train, evaluate, and optimize large language models, multimodal models, transformers, CNNs, RNNs, and diffusion architectures.
  • Research quantization, compression, distillation, pruning, hardware-aware training, and on-device deployment.
  • Prototype model architectures, training methods, and inference strategies for distributed AI.
  • Build datasets, benchmarks, and experimental frameworks to validate model performance.
  • Collaborate with research, applied AI, and platform engineering teams to integrate findings into production systems.
  • Analyze experiments, document findings, contribute to papers, and present technical work.

Requirements

  • 4+ years of experience, including graduate research, in machine learning research, AI model development, or a related field.
  • Strong expertise in deep learning architectures and experience training and fine-tuning large-scale models.
  • Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or JAX.
  • Experience building datasets, designing experiments, and validating ML model performance.
  • Strong understanding of optimization techniques, including quantization, distillation, pruning, and hardware-aware training.
  • Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field.

Nice to have

  • Master’s or PhD in Machine Learning, Computer Science, AI, or a related field.
  • Experience with distributed training, edge inference, on-device ML, generative AI, reinforcement learning, or multimodal learning.
  • Familiarity with privacy-preserving ML, including federated learning.
  • Academic publications, patents, or open-source ML contributions.
  • Experience in a fast-paced, high-growth startup environment.

Culture & Benefits

  • Values centered on truth, ownership, tenacity, and humility.
  • Health, dental, and vision benefits for eligible U.S.-based employees.
  • 401(k) match, equity options, supplemental life insurance, and parental leave.
  • $200/month Health & Wellness stipend and $500/year Function Health subscription.
  • Continuing Education support, Flexible Time Off, and free parking for in-office employees.
  • Benefits for employees hired outside the United States may vary by local law and employment entity.

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