About Appier 

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 further improve bidding strategies, audience targeting and creative optimization by deep-diving RTB ecosystem including SSP/DSP/MMP to design the strategy, enhancing user signals or applying advanced deep learning model

What You’ll Work On

• Deep-dive the RTB ecosystem to identify the potential direction and decide the bidding strategy
• Leverage advance deep learning model to improve bidding/audience model performance
• Co-work with teams to improve real-time/long-term user interaction signal collection and to further improve model performance

What We’re Looking For

• Master’s or PhD’s degree in Computer Science, Machine Learning, Statistics, or related field.
• 3+ years of industry experience on RTB ecosystem
• Proficiency in Python and SQL experience with modern ML frameworks and deep learning model (PyTorch, TensorFlow, etc.).
• Strong ownership and collaboration skills.

#LI-AK1

About Appier 

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).

#LI-AK1

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

AI is reshaping how brands connect with consumers — and at Appier, we’re at the forefront. Our Playable Ads team builds AI-powered ad experiences — from interactive playable formats to video ads — that drive dramatically higher engagement and conversion for the world’s leading apps and games. We’re looking for a Senior Machine Learning Scientist to push the boundaries of what’s possible — applying cutting-edge ML, generative AI, and optimization techniques to create smarter, more compelling ad creatives at scale.

If you’re excited about turning the latest advances in AI into products that reach millions of users, and you thrive at the intersection of research and real-world impact, we’d love to talk.

What You’ll Work On

• Apply ML and generative AI techniques to problems such as creative optimization, user behavior prediction, engagement modeling, and dynamic content generation for various creative formats.
• Own the end-to-end ML lifecycle — from problem framing and experimentation through to production deployment and continuous improvement.
• Collaborate closely with product, engineering, and design teams to translate business goals into well-defined ML solutions.
• Conduct offline and online evaluation, A/B testing, and performance monitoring to continuously improve model quality and business impact.
• Stay current with the latest research in areas like LLMs, multimodal models, reinforcement learning, and recommendation systems, and proactively propose innovative applications to the team.
• Mentor fellow scientists and contribute to the team’s technical standards and culture.

What We’re Looking For

[Minimum qualifications]

• Master’s or Ph.D. in Computer Science, Machine Learning, Mathematics, Electrical Engineering, or a related field.
• Solid understanding of modern ML models and algorithms, with hands-on experience in at least one area such as prediction/optimization, generative models, recommendation systems, computer vision, or reinforcement learning.
• Proficient in Python and ML frameworks such as PyTorch or TensorFlow.
• Practical experience taking ML models from prototype to production, including pipeline development and performance monitoring.
• Strong analytical and problem-solving skills with the ability to diagnose model behavior and improve training pipelines.
• Clear communicator who can explain technical ideas to both technical and non-technical stakeholders and enjoys working in a fast-paced, collaborative environment.
• Proficient in using LLM-powered development tools (e.g., GitHub Copilot, Cursor, ChatGPT) to accelerate productivity.
• Ability to balance cutting-edge research with time-to-market constraints, delivering iterative PoCs that validate product hypotheses and translate into production-ready solutions.

[Preferred qualifications]

• Publications in top AI/ML conferences or journals (e.g., NeurIPS, ICML, ICLR, CVPR, KDD, RecSys).
• Experience in the advertising technology or MarTech domain.
• Contributions to open-source projects or active involvement in research communities.

#LI-AK1

About Appier 

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.

Our engineering team has a solid technical background, which would be a great environment for a skilled engineer.

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.
• 5+ 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).

Language

Fluent in English or Chinese.

#LI-AK1

About Appier 

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.

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).

#LI-AK1

About Appier 

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.

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 build identify graph to enrich unified customer profile and also identify high purchase value users to drive ROAS by machine learning model.

What You’ll Work On

• Leverage scientific methods to build identify graph and identify high-value users
• Drive online experiments to continuously improve ROAS
• Own the project independently.
• Partner with product stakeholder, backend and frontend to provide measurement solution for our customers.

What We’re Looking For

• Master’s or PhD’s degree in Computer Science, Machine Learning, Statistics, or related field.
• 3+ years of industry experience on identify graph, ID mapping and cross-device mapping in digital Ads related fields, and generate mapping and profile under large-scale data.
• Proficiency in Python and SQL experience with modern ML frameworks (PyTorch, TensorFlow, etc.).
• Strong ownership and collaboration skills.

#LI-AK1

About Appier 

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 measure ads incrementality on different type of traffic, creative, users, and also improve campaign efficiency on combination having good incrementality by machine learning model and AI automation.

What You’ll Work On

• Leverage scientific methods to improve ads measurement.
• Drive online experiments to continuously improve ads effectiveness.
• Own the project independently.
• Partner with product stakeholder, backend and frontend to provide measurement solution for our customers.

What We’re Looking For

• Master’s or PhD’s degree in Computer Science, Machine Learning, Statistics, Econometrics, or related field.
• 3+ years of industry experience on causal inference, incrementality, marketing mix modeling or other measurement solutions on digital Ads related fields, and understand the assumption and difference across methods.
• Proficiency in Python and SQL experience with modern ML frameworks (PyTorch, TensorFlow, etc.).
• Strong ownership and collaboration skills.

Language

Fluent in English or Chinese.

#LI-AK1