We are seeking a highly skilled and motivated Machine Learning Engineer to join our dynamic team. As a Machine Learning Engineer, you will play a crucial role in developing, deploying, and optimizing cutting-edge artificial intelligence and machine learning models. The ideal candidate should have a strong background in computer science, practical experience in AI/ML, and a proven track record of contributing to successful projects. If you are passionate about pushing the boundaries of technology and making a significant impact, we want to hear from you.

Responsibilities

• Develop, implement, and optimize machine learning models for a variety of applications, with a focus on natural language processing and deep learning.
• Collaborate with cross-functional teams to design and deploy ML infrastructure, ensuring scalability, reliability, and efficiency.
• Utilize one or more general-purpose programming languages such as Python, Java, or C/C++ to build robust and scalable machine learning solutions.
• Deploy and serve deep learning models in production environments, leveraging accelerator frameworks like CUDA, TensorRT, and Triton Inference Server.
• Work with large language models (LLMs) such as LLaMA and GPT3 to create innovative solutions for real-world challenges.
• Conduct model optimization using algorithms like LoRA and QLoRA to enhance performance and efficiency.
• Stay abreast of the latest advancements in machine learning, AI, and related fields, and incorporate cutting-edge techniques into projects.
• Contribute to the research community by publishing original and impactful research in top-tier conferences and journals, including but not limited to ACL, EMNLP, NAACL, EACL, LREC, CoNLL, IJCNLP, NIPS, and AAAI.
  
  

Requirements

• Bachelor's degree in computer science or a related field.
• Minimum of 2 years of relevant industry experience in artificial intelligence and machine learning.
• Proficiency in one or more general-purpose programming languages, such as Python, Java, or C/C++.
• Strong experience in developing, deploying, and optimizing machine learning models, infrastructure, and deep learning solutions.
• Hands-on experience with serving deep learning models in production using accelerator frameworks like CUDA, TensorRT, and Triton Inference Server.
• Familiarity with large language models (LLMs) like LLaMA and GPT3
• Model optimization experience using algorithms like LoRA and QLoRA is a plus.
• Demonstrated ability to contribute to the research community, with a track record of publications in top-tier conferences and journals.
  
  

This job was posted by Ruppal Agarwal from Salesken.