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Senior Machine Learning Research Scientist

1 month ago

Reston, Virginia, United States Acceler8 Talent Full time

About Acceler8 Talent

We are a cutting-edge startup focused on building innovative AI solutions for the highly complex electronics and semiconductor industry. Based in the SF Bay Area, we collaborate with top investors and some of the world's largest semiconductor companies. Our team is composed of former Stanford researchers and engineers from Nvidia, Apple, and Google, including multiple Olympiad and ICPC medalists.

About the Role

As a Senior Machine Learning Research Scientist, you will be at the forefront of developing and optimizing both open-source and closed-source models. You will structure data for training complex models and design innovative search and retrieval algorithms. Your work will be crucial in creating and implementing model evaluations that set new standards in the industry. This role is perfect for someone who thrives in a fast-paced, challenging environment and is excited about solving real-world problems.

What We Offer

  • Competitive salary and benefits package
  • Opportunities for professional growth and development
  • Collaborative and inclusive work environment
  • Access to state-of-the-art technology and resources
  • Flexible working hours and remote work options
  • Supportive team culture focused on innovation and excellence

Key Responsibilities

  • Develop and evaluate extensive systems comprising interconnected LLMs, NLP models, and retrieval algorithms
  • Structure data for training complex models
  • Build and optimize both open-source and closed-source models, considering various constraints
  • Design and execute innovative search and retrieval algorithms
  • Create and implement model evaluations
  • Build the world's most knowledgeable AI model in semiconductors and electronics

Keywords: LLM, Large Language Model, Machine Learning, Deep Learning, ML, Neural Networks, NLP, Natural Language Processing, Applied Scientist, Open-Source, OSS, Quantization, Sparsity, Pruning, Neural Architecture Search, Hardware Acceleration, Training, Inference, Tensorflow, PyTorch, JAX