Роль четко определена с акцентом на передовые исследования в области ИИ и высокой зарплатой, что делает ее привлекательной для квалифицированных инженеров.
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Высокая зарплатаПередовой доменЧетко определенная рольГибридная модель работы
Оценка от Hirify AI
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Hirify AI/Оригинал
TL;DR
Research Engineer (AI): Building large-scale ML systems from the ground up with an accent on making safe, steerable, trustworthy systems. Focus on improving throughput and efficiency, running and designing scientific experiments, or improving our dev tooling.
Location: Hybrid in New York City, Seattle, or San Francisco; staff are expected to work from one of the offices at least 25% of the time.
Annual salary: $350,000–$500,000 USD
Company
Anthropic builds reliable, interpretable, and steerable artificial intelligence systems intended to be safe and beneficial for users and society.
What you will do
Build and improve large-scale machine learning systems, code, and infrastructure.
Improve cluster reliability, training throughput, and computational efficiency for large research jobs.
Design and run scientific experiments in collaboration with research teams.
Optimize attention mechanisms and compare the compute efficiency of Transformer variants.
Prepare large datasets for model consumption and scale distributed training jobs to thousands of GPUs.
Develop fault-tolerance strategies and interactive visualizations for language-model attention.
Requirements
Significant software engineering experience.
Bachelor’s degree or an equivalent combination of education, training, and experience.
Education, training, or professional experience in a field relevant to the role.
Results-oriented approach, flexibility, strong communication skills, and interest in machine learning research.
Care about the societal impacts and safety of AI systems.
Ability to work from one of Anthropic’s US offices at least 25% of the time.
Nice to have
Experience with high-performance, large-scale machine learning systems.
Experience with GPUs, Kubernetes, PyTorch, or operating system internals.
Experience with language modeling using Transformers or reinforcement learning.
Experience with large-scale ETL.
Culture & Benefits
Collaborative research environment centered on a small number of large-scale efforts.
Frequent research discussions and emphasis on communication and impact.
Flexible working hours and an office environment for collaboration.
Visa sponsorship is available, although sponsorship cannot be guaranteed for every role or candidate.
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