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ML Optimization Engineer - Gonka Network Mining Operations

Obscuracompute.com
≈ 155,4 тыс.–310,8 тыс. ₽ · 1,7 тыс.–3,5 тыс. €
2 000 – 4 000 $
🌍 Удалённо
Senior
Полная занятость
Описание вакансии
About Us

We are a leading participant in the Gonka decentralized AI network (​), leveraging high-performance GPU infrastructure to maximize mining rewards. We’re seeking an ML Optimization Engineer to help us achieve superior efficiency and weight in the Gonka ecosystem.

Key Responsibilities
Implement advanced inference optimizations (speculative decoding, quantization, attention modifications, etc.) to maximize mining weight — techniques already proven to achieve double weight with identical GPUs by other participants
Fine-tune Docker configurations for various GPU models based on available registry
Develop custom optimization strategies that balance throughput and quality
Create and maintain custom Docker images optimized for specific GPU architectures
Design and implement systems for stable and scalable mining of Gonka and other protocols
Develop optimized images for Tenstorrent AI ASICs to expand our hardware ecosystem beyond current GPU deployment
Migrate Python code and VLLM implementations to new VLLM images and adapt them for specific GPU cards
Required Qualifications
Proven experience with large language model optimization techniques
Strong understanding of transformer architectures and attention mechanisms
Proficiency with PyTorch, CUDA, and GPU optimization techniques
Experience with vLLM, FlashInfer, or similar inference optimization frameworks
Familiarity with Docker containerization and GPU workload management
Preferred Qualifications
Experience with Claude Code Max (will be provided if needed)
Previous experience with Gonka or similar decentralized AI networks
Background in competitive ML or distributed systems optimization
Experience with NVIDIA GPU architectures (B200/B300/H200/H100/A100)
Knowledge of Tenstorrent AI ASICs or other specialized AI hardware
What We Offer
Opportunity to work with cutting-edge AI infrastructure
High performance-based bonuses tied to achieved weight improvements
Potential for full-time position with percentage of mining profits
Flexible remote work environment
Access to high-end GPU hardware for experimentation

Application Process: Intrested candidates should submit their resume along with a brief description of their relevant experience in ML optimization or performance enhancement ideas.

AI-помощник
ИсточникGeekJob
Опубликовано6 июл.
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