Apache Spark, Artificial Intelligence (AI), Computer Science, Data Cleaning, Data Processing, Diversity, Environmental Research, Machine Learning, Modeling Languages, Natural Language Processing (NLP), Research & Development (R&D), Research Skills, Team Player
AI Researcher – Large Language Models (LLMs)
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Join our client's Research and Development (AI/ML Team)<\/b> in Redmond, where innovation meets impact. Their team is at the forefront of AI research, specialising in cutting -edge advancements in Large Language Models (LLMs) and generative AI. They offer a dynamic, collaborative environment where visionary researchers drive transformative projects with real -world impact.
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What You'll Do<\/b>
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As an AI Researcher<\/b>, you will:
<\/p>- Conduct pioneering research on LLMs, focusing on architecture, training, optimization, and fine -tuning methodologies.
<\/li> - Design and implement advanced data preparation workflows, including data cleaning, augmentation, and synthetic data generation.
<\/li> - Develop scalable training pipelines for LLMs using distributed computing and state -of -the -art optimization algorithms.
<\/li> - Explore multi -modal AI systems, integrating LLMs with other data types such as vision and audio.
<\/li> - Publish high -impact research in top -tier journals and conferences like IEEE, enhancing the field of AI.
<\/li> - Mentor junior researchers, sharing best practices to inspire impactful AI innovations.
<\/li> - Stay at the cutting edge of LLM advancements, fostering continuous learning and innovation within the team.
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Requirements<\/h3>
Required Qualifications<\/b>:
<\/h4>- Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field, with research emphasis on NLP, LLMs, or generative AI.
<\/span><\/li> - Demonstrated expertise in training and fine -tuning large -scale language models (e.g., GPT, BERT, T5).
<\/span><\/li> - Strong publication record in IEEE or equivalent journals/conferences related to LLM training, data preparation, or synthetic data generation.
<\/span><\/li> - Proficiency in deep learning frameworks such as TensorFlow, PyTorch, or JAX.
<\/span><\/li> - Hands -on experience in large -scale data processing and distributed training techniques.<\/span>
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Preferred Qualifications<\/b>:
<\/p>- Experience with RAG and multi -modal AI systems.
<\/li> Expertise in domain -specific LLM fine -tuning and data augmentation.
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Familiarity with synthetic data generation tools and platforms like Apache Spark or Dask.
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Proven leadership and mentoring abilities in a research settings.
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Benefits<\/h3>
What Our Client Offers<\/b>
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