LLM Research Scientist (Intern)

2 Months ago • Upto 1 Years • Artificial Intelligence • Undisclosed

About the job

Job Description

As an LLM Research Scientist Intern at Appier, you'll contribute to developing and improving cutting-edge language models. Responsibilities include collaborating with senior scientists on experiments, conducting literature reviews, developing algorithms for training LLMs, analyzing results, participating in team meetings, documenting findings, and assisting in model evaluation. The internship requires a commitment of 2-5 days/week (16-40 hours) for at least 6 months. There's a potential for a full-time position afterward. The role involves hands-on experience in AI research and contributing to groundbreaking advancements in natural language understanding and generation.
Must have:
  • Graduate program enrollment (CS, AI, ML)
  • Strong Python, TensorFlow, or PyTorch skills
  • Solid understanding of ML concepts
  • Excellent problem-solving skills
  • Teamwork and communication skills
Good to have:
  • NLP/ML research experience
  • Deep learning framework familiarity
  • Large-scale data processing experience
  • Strong mathematical background
  • AI/NLP publications

About Appier 

Appier is a software-as-a-service (SaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180).
Visit www.appier.com for more information.

 

About the role

As a Large Language Model (LLM) Research Scientist Intern, you will be an integral part of our research team, contributing to the development and enhancement of cutting-edge language models. You will have the opportunity to work on various projects aimed at advancing natural language understanding and generation capabilities. This internship offers a unique chance to gain hands-on experience in the field of artificial intelligence and contribute to groundbreaking research.

We are currently looking for individuals who can commit to an internship schedule of 2-5 days (16-40 hours) per week. This internship opportunity entails a minimum duration of 6 months, beginning from the present date. We advise prospective applicants to carefully assess their availability for this commitment before submitting their applications.

After the internship, there is an opportunity to transition from an intern to a full-time position.

 

Responsibilities

  • Collaborate with senior research scientists to design and implement experiments for improving LLM performance.
  • Conduct literature reviews and stay up-to-date with the latest advancements in natural language processing (NLP) and machine learning (ML).
  • Develop and implement algorithms for training and fine-tuning large language models.
  • Analyze and interpret experimental results to draw meaningful conclusions and insights.
  • Participate in team meetings and contribute ideas to drive innovation in LLM research.
  • Document research findings and contribute to academic publications and technical reports.
  • Assist in the evaluation and benchmarking of LLM models using standard NLP datasets.

 

About you

[Minimum qualifications]

  • Currently enrolled in a graduate program (Bachelor's, Master's, or Ph.D.) in computer science, artificial intelligence, machine learning, or a related field.
  • Strong programming skills in languages such as Python, TensorFlow, or PyTorch.
  • Solid understanding of machine learning concepts and algorithms.
  • Excellent problem-solving skills and analytical thinking.
  • Ability to work independently as well as collaboratively in a team environment.
  • Good communication skills and the ability to present complex ideas effectively.

[Preferred qualifications]

  • Previous research experience in natural language processing or machine learning.
  • Familiarity with deep learning frameworks and libraries.
  • Experience with large-scale data processing and distributed computing platforms.
  • Strong mathematical background, including proficiency in linear algebra and probability theory.
  • Publications in top-tier conferences or journals related to artificial intelligence or NLP.
  • Demonstrated interest in advancing the state-of-the-art in language understanding and generation.
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