SkillTrendLab
中文
Skill · LLM applications

Fine-tuning

Continuing to train an existing model on your own data.

8.6%
of core AI postings mention it
304
postings
219
companies
—
30-day change · from 2nd edition

Which roles ask for it

Share of each role's postings that mention this skill.

  1. LLM / NLP Engineer
    63 postings
    36.0%
  2. AI Engineer
    178 postings
    10.2%
  3. AI Researcher
    6 postings
    10.0%
  4. MLOps / Platform Engineer
    3 postings
    7.9%
  5. Data Scientist
    11 postings
    7.3%
  6. Computer Vision Engineer
    8 postings
    7.1%
  7. Algorithm Engineer
    13 postings
    4.0%
  8. Smart Manufacturing / AOI
    4 postings
    1.8%
  9. Edge AI / Hardware Engineer
    2 postings
    1.6%
  10. AI Product / Project Manager
    4 postings
    1.3%

Skills that appear with it

Share of the postings mentioning Fine-tuning that also mention each skill.

  1. Python
    Languages
    84.2%
  2. LLM
    LLM applications
    83.5%
  3. RAG
    LLM applications
    54.6%
  4. Machine Learning
    Machine learning
    48.7%
  5. PyTorch
    Frameworks
    46.7%
  6. System Architecture
    Methods and process
    45.1%
  7. Generative AI
    LLM applications
    43.4%
  8. AI Agents
    LLM applications
    42.4%
  9. Deep Learning
    Machine learning
    42.4%
  10. Prompt Engineering
    LLM applications
    39.1%
  11. Docker
    DevOps
    36.8%
  12. Git
    Tools
    35.2%

Industries and places

Share of this skill's postings.

Industry
  1. Software & Internet
    131
    43.1%
  2. Electronics & Hardware
    54
    17.8%
  3. Semiconductor
    31
    10.2%
  4. Finance & Insurance
    23
    7.6%
  5. Telecom, Media & Digital Content
    13
    4.3%
  6. Manufacturing
    12
    4.0%
  7. Professional Services
    11
    3.6%
  8. Healthcare & Biotech
    8
    2.6%
  9. Wholesale, Retail & E-commerce
    8
    2.6%
  10. Consulting & Marketing Services
    6
    2.0%
  11. Construction & Real Estate
    4
    1.3%
  12. Government & Nonprofit
    2
    0.7%
Place
  1. Taipei
    172
    56.6%
  2. New Taipei
    34
    11.2%
  3. Hsinchu County
    22
    7.2%
  4. Hsinchu City
    21
    6.9%
  5. Kaohsiung
    15
    4.9%
  6. Taichung
    15
    4.9%
  7. Taoyuan
    9
    3.0%
  8. Miaoli
    6
    2.0%
  9. Changhua
    4
    1.3%
  10. Yunlin
    3
    1.0%
  11. Hualien
    1
    0.3%
  12. Tainan
    1
    0.3%

Where this number is read from

Of the 304 postings, how many were found through the employer's own skill tags, the title, and the job description. A posting can carry more than one kind of evidence, so the three add up to more than the posting count.

  1. Employer's skill tags
    0
  2. Job title
    1
  3. Job description
    304
The data on this page
Data as of
September 11, 2026
Core AI postings this edition
3,523
Method version
2026.09.1

This page is not indexed yet: change needs a second edition.

Methodology →All skills →