1 час назад
Research Engineer (AI)
210 000 - 320 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Research Engineer (AI): Developing novel model architectures, training objectives, and distributed training systems for large-scale deep learning with an accent on algorithmic efficiency, GPU cluster utilization, and data pipelines. Focus on reproducing and extending state-of-the-art research, optimizing communication and training performance, and translating mathematical concepts into reliable production code.
Location: San Mateo or New York, United States
Salary: $210,000–$320,000 per year, plus equity
Company
provides a platform for building, training, and serving specialized AI models across text, image, embedding, audio, and multimodal workloads.
What you will do
- Explore new model architectures, training objectives, and optimization techniques through hypothesis-driven experiments.
- Implement and reproduce results from recent machine learning research, identify limitations, and extend methods to larger datasets and models.
- Design, implement, and maintain high-performance distributed training systems for large GPU clusters.
- Optimize training loops, data loaders, communication overhead, and GPU cluster utilization.
- Translate mathematical research concepts into clean, reliable, and efficient code.
- Collaborate with research scientists on tooling, hardware-aware experiments, and infrastructure improvements.
Requirements
- Strong programming skills in Python, C++, or Rust.
- Practical knowledge of PyTorch, JAX, or TensorFlow.
- Experience with distributed systems and parallel computing, including technologies such as CUDA, NCCL, or MPI.
- Strong foundation in linear algebra, calculus, probability, and statistics.
- Experience implementing complex deep learning algorithms from scratch.
- Work location: San Mateo or New York, United States.
Nice to have
- Master’s or PhD in computer science, machine learning, physics, mathematics, or a related field, or equivalent industry experience.
- Experience with CUDA, Triton, or hardware co-design.
- Familiarity with large language model training.
- Familiarity with inference and inference engines such as SGLang and vLLM.
Culture & Benefits
- Work on AI infrastructure, including low-latency inference and scalable model serving.
- Build production AI technology using open models across multiple modalities.
- Collaborate with engineers and AI researchers on high-impact technical problems.
- Equity is included in the compensation package.
- Inclusive, equal-opportunity working environment.
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