Time since we first saw it
Day 29
Similar jobs usually come down between day 6 and day 70.
At Appier, jobs usually come down by about day 77.
From 4,444 similar postings that came down, and 10 of Appier’s. Coming down is not always a hire.
(Senior) Machine Learning Scientist (Modeling & Evaluation)
Taipei, Taiwan
Live, first seen by us 29 days ago- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingDesign, develop and deploy optimization solutions built on ML models
Build reliable evaluation methods for LLM output and decide if results apply to real conditions
Design A/B tests with real traffic to validate your own hypotheses
Turn product goals and customer needs into clear problems and integrate validated methods
Monitor solutions after launch and communicate risks and trade-offs
From the employer’s posting
Design, develop, and deploy optimization solutions built on ML models and evaluation
Build reliable evaluation methods for LLM output to measure the quality and impact of solutions
Form your own hypotheses, then design A/B tests that use real traffic to validate them.
Work with PMs and engineers to turn product goals and customer needs into clear problems and priorities, and integrate validated methods into the product.
Monitor solutions after launch, and proactively communicate risks, trade-offs, and progress.
What you’ll bring
All qualificationsPreferred experience
- Experience leading projects
- Ability to form hypotheses and validate them: design experiments and A/B tests, interpret results, and take ownership of conclusions
Qualification wording
Experience leading projects
Ability to form hypotheses and validate them: design experiments and A/B tests, interpret results, and take ownership of conclusions
Education & alternatives
What We're Looking For (Minimum Qualifications) - Master's or PhD degree in Computer Science, Machine Learning, Mathematics, Electrical Engineering, or related fields - At least 2 years of experience in machine learning or engineering roles (5+ years preferred)
About Appier
Appier (TSE: 4180) is an AI-native Agentic AI as a Service (AaaS) company that empowers businesses to create value through cutting-edge AdTech and MarTech solutions.
In the employer’s words · Read in context
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 7, 202629 days ago
- Recorded sightings
- 22
- Last seen by us
- Nov 5, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Appier is hiring
15 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Its jobs tend to stay up a long time
- 7% of open jobs were reposted
See how this role fits your experience
Add your resume to compare the role’s scope, tools and requirements with your experience.
Your next step
Complete your application on job-boards.greenhouse.io. The employer’s form will show what is required.
Applying through Greenhouse
- No account needed: the form is one page, with an “Autofill my application” option that reads your resume.
- Greenhouse doesn’t read resumes over 2.5 MB, or details placed in a header, footer, text box, table or second column. The file still attaches, but a recruiter has to type you in by hand.
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Demand for ML Engineer roles
New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
About Appier
Appier (TSE: 4180) is an AI-native Agentic AI as a Service (AaaS) company that empowers businesses to create value through cutting-edge AdTech and MarTech solutions. Founded in 2012 with the vision of “Making AI Easy by Making Software Intelligent,” Appier helps businesses turn AI into ROI through its Ad Cloud, Personalization Cloud, and Data Cloud—each powered by Agentic AI that enables autonomous, adaptive, and real-time decision-making. Today, Appier operates 17 offices across APAC, the US, and EMEA, and is listed on the Tokyo Stock Exchange. Learn more at www.appier.com.
About the Role
We are looking for a Machine Learning Scientist (Modeling & Evaluation) to join the Enterprise Solution Science Team and help enterprises turn AI into real ROI.
In this role, you will be responsible for end-to-end development, from problem definition to driving models and solutions into production.
What You'll Work On
- Design, develop, and deploy optimization solutions built on ML models and evaluation, to improve efficiency and quality.
- Work with PMs and engineers to turn product goals and customer needs into clear problems and priorities, and integrate validated methods into the product.
- Build reliable evaluation methods for LLM output to measure the quality and impact of solutions, and decide if the results apply to real-world conditions.
- Form your own hypotheses, then design A/B tests that use real traffic to validate them.
- Follow the latest research and industry solutions, evaluate them in our own context, and propose new approaches. Decide what to build in-house and what to adopt.
- Monitor solutions after launch, and proactively communicate risks, trade-offs, and progress.
- (Optional) Mentor junior scientists and interns, if the need arises.
What We're Looking For (Minimum Qualifications)
- Master's or PhD degree in Computer Science, Machine Learning, Mathematics, Electrical Engineering, or related fields
- At least 2 years of experience in machine learning or engineering roles (5+ years preferred)
- Hands-on experience with ML models (including classification, regression, ranking, and retrieval) and quality evaluation (including LLM-as-a-judge), a solid foundation in statistics, and the ability to explain how these techniques relate to business impact
- Impact-driven mindset: able to judge task priority, collaborate across functions, and proactively drive work forward and surface risks
- AI-native development: work daily with coding agents that read the codebase, run tests, and iterate on their own, while you set the scope and review the diffs. Can explain and correct what the agent produced
Preferred Qualifications
- Experience leading projects
- Ability to form hypotheses and validate them: design experiments and A/B tests, interpret results, and take ownership of conclusions
- Background in embeddings and causal inference
- Engineering experience with AI / LLM applications (for example, serving and integration)
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Taipei, Taiwan
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.