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5 hours ago
Responsibilities: Implement quantization techniques to optimize model performance and efficiency. Experience with inference optimizations at node and cluster scale Experience developing, modifying, optimizing inference frameworks such as vLLM, SGLang. Optimize multi-modal LLM deployments, prompt caching, RAG workflows, etc. Collaborate with HW and SW teams to drive innovations and optimizations into the product deployments Stay up-to-date with the latest advancements in machine learning and AI technologies, and apply them to improve our products and services. Requirements: Bachelor's or Master's or Ph.D. degree in Computer Science, Engineering, or a related field. Must have strong background in quantization and model optimization techniques. Experience in deploying machine learning models at scale in production environments. Proficiency in PyTorch. Solid understanding of machine learning algorithms and their implementation on accelerators. Excellent problem-solving skills and the ability to work independently as well as part of a fast paced team in a startup environment. Strong communication skills to effectively convey technical concepts to non-technical stakeholders. Preferred Qualifications / Experience: Experience with fine-tuning and distillation of large language models (LLMs) Experience with cloud platforms such as AWS, Google Cloud, or Azure. ·
Familiarity with MLOps practices and tools for model deployment and monitoring. Benefits: ·
Competitive salary and benefits package. ·
Opportunity to work on cutting-edge AI technology. ·
Collaborative, dynamic and inclusive work environment. ·
Professional growth and development opportunities. How to Apply:
Interested candidates are invited to submit their resume and a cover letter detailing their relevant experience and why they are a good fit for this role to careers@turiyamai.com
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