4 дня назад
Member of Technical Staff (AI Research)
200 000 - 300 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Member of Technical Staff (AI Research) (LLMs and multimodal systems): Conducting foundational research and developing model architectures, training methods, and optimization techniques with an accent on efficiency, accuracy, reliability, and scalability. Focus on transitioning research prototypes into production-grade AI systems, analyzing performance bottlenecks, and advancing large-scale model training and inference.
Location: San Mateo or New York, United States
Salary: $200,000–$300,000 per year
Company
provides a platform for building, training, and serving specialized AI models across text, image, embedding, audio, and multimodal workloads.
What you will do
- Conduct foundational research advancing the capabilities, efficiency, and reliability of LLMs and multimodal systems.
- Design, implement, and evaluate model architectures, training methods, and optimization techniques.
- Collaborate with engineering teams to transition research prototypes into production-grade systems.
- Analyze empirical results, identify performance bottlenecks, and improve model quality.
- Contribute ideas and research directions from doctoral work to the internal research agenda.
Requirements
- PhD completed within the last 6 months or expected by December 2026 in Computer Science, Machine Learning, Computational Physics, Mathematics, Electrical Engineering, or a related field.
- Research background in AI, machine learning, physics, or a related area, demonstrated through a dissertation, publications, or research projects.
- Experience solving analytical problems using analytical and quantitative approaches.
- Ability to communicate research to audiences with different backgrounds.
- Proficiency in Python, C/C++, or similar programming languages.
- Hands-on experience with PyTorch, JAX, TensorFlow, or similar ML frameworks.
Nice to have
- First-author publications at leading peer-reviewed conferences or journals such as NeurIPS, ICML, ICLR, or MLSys.
- Industry research internships or open-source contributions to ML systems, model training, or inference projects.
- Experience with large-scale model training, distributed systems, GPU kernel development, or inference optimization.
- Experience taking research code beyond the prototype stage.
Culture & Benefits
- Work on AI infrastructure, low-latency inference, and scalable model serving.
- Collaborate with experienced engineers and AI researchers on emerging technologies.
- Receive mentorship from a senior researcher and work on a real research problem from the beginning.
- See research models deployed in production for leading companies.
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