Design, implement, and productionize state-of-the-art ML models for campaign outcomes
Analyze large-scale user and auction data to find predictive patterns and alpha signals
Collaborate with engineering, product, and data teams to define roadmaps and deliver solutions
Improve system performance through offline experimentation and online testing such as A/B tests
From the employer’s posting
Design, implement, and productionize state-of-the-art ML models to improve campaign outcomes.
Analyze large-scale user and auction data to discover predictive patterns and alpha signals that enhance bidding and personalization.
Collaborate cross-functionally with engineering, product, and data teams to identify opportunities, define roadmaps, and deliver impactful solutions.
Continuously improve system performance through offline experimentation and online testing (e.g., A/B tests, incremental learning).
Education & alternatives
What We’re Looking For
- Bachelor’s degree in Computer Science, Mathematics, EE, or related field; Master’s or PhD preferred.
- 4+ years of industry experience in ad tech, with a focus on performance optimization.
About Appier
Appier is an AI-native Agentic AI as a Service (AaaS) company that uses artificial intelligence (AI) to power business decision-making.
Open 7 monthsWe first saw this posting 211 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
Status in our records
Live
First seen by us
Apr 8, 2026211 days ago
Recorded sightings
217
Last seen by us
Nov 5, 2026
Apr 8, 2026today
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 211
670
Up longer than most. Similar jobs usually come down between day 6 and day 70.
Well past Appier’s usual: its jobs 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.
Appier is hiring
15 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
Python
PyTorch
TensorFlow
Where the posting names them
- Proven experience in applied machine learning, especially in CTR prediction, recommendation systems.
- Proficiency in Python and experience with modern ML frameworks (PyTorch, TensorFlow, etc.).
- Strong ownership and collaboration skills—able to lead end-to-end projects across product, data, and engineering.
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.
New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
August 17Last week
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.
Appier is an AI-native Agentic AI as a Service (AaaS) 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.
Open to overseas candidates/Visa Support
This position is based in Tokyo, Japan. For international candidates, Appier's Japan office provides visa sponsorship to ensure a smooth transition to Japan.
The Impact You’ll Make at Appier
Appier is seeking a Senior Machine Learning Scientist to join our Advertising Cloud Optimization team, which leads the development of core machine learning algorithms driving campaign efficiency and advertiser ROI. Our programmatic advertising platform operates at a massive scale, handling over multi millions queries per second (QPS), all powered by our proprietary deep learning models for bidding, pricing, and personalized content delivery.
In this role, you’ll directly impact the efficiency and profitability of ads campaigns by improving models for bidding, pricing, and personalized content recommendation, while ensuring system robustness and scalability in a dynamic market environment.
What You’ll Work On
Design, implement, and productionize state-of-the-art ML models to improve campaign outcomes.
Analyze large-scale user and auction data to discover predictive patterns and alpha signals that enhance bidding and personalization.
Collaborate cross-functionally with engineering, product, and data teams to identify opportunities, define roadmaps, and deliver impactful solutions.
Continuously improve system performance through offline experimentation and online testing (e.g., A/B tests, incremental learning).
What We’re Looking For
Bachelor’s degree in Computer Science, Mathematics, EE, or related field; Master’s or PhD preferred.
4+ years of industry experience in ad tech, with a focus on performance optimization.
Proven experience in applied machine learning, especially in CTR prediction, recommendation systems.
Proficiency in Python and experience with modern ML frameworks (PyTorch, TensorFlow, etc.).
Strong ownership and collaboration skills—able to lead end-to-end projects across product, data, and engineering.
Bonus: Experience working on high-throughput, low-latency real-time systems (e.g., RTB engines, stream inference).
Selected passages from the saved posting. Check the full description for conditions and exceptions.
Pay
No pay amount identified in the saved description.
Location & working pattern
Tokyo, Japan
Working pattern and location restrictions need checking in the full posting.
Work authorization
Appier is an AI-native Agentic AI as a Service (AaaS) 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.
Open to overseas candidates/Visa Support
This position is based in Tokyo, Japan. For international candidates, Appier's Japan office provides visa sponsorship to ensure a smooth transition to Japan.
The Impact You’ll Make at Appier