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 Intern to join the Enterprise Solution Science Team.
This team focuses on applying cutting-edge ML technologies to real-world marketing problems by combining them with omnichannel customer data.

We are currently looking for individuals who can commit to an internship schedule of 2~4 days (16~32 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.

[ Due to the hybrid work model, this position cannot be fully remote and requires working in the Taiwan office. ]

Responsibilities

• Work on one of the following ML or LLM topics: user prediction, recommendation, agents, and chatbots.
• Collaborate closely with senior ML scientists to define ML problems, algorithm development, conduct evaluations, monitoring, and continuous optimization.
• Stay up to date with the latest research and proactively propose innovative applications.

About you

[Minimum qualifications]

• Bachelor's degree in Computer Science, Machine Learning, Mathematics, Electrical Engineering, or related fields. (Master's degree preferred)
• 2+ years of experience in ML or LLM.
• Proficient in Python.
• Proficient in one of the below
  1.Core ML and deep learning concepts: feature engineering, recommendation, regression, classification, clustering, etc.
  2.LLM applications development techniques: RAG, agent, chatbots.
• Able to evaluate models with systematic and quantitative analysis.
• Strong data intuition and familiarity with basic statistical concepts.

[Preferred qualifications]

• Impact-driven mindset, strong analytical and problem-solving skills, and a continuous passion for learning cutting-edge technologies.
• Proficient in using LLM-powered tools (e.g., Github Copilot, ChatGPT) to boost development productivity.

#LI-AK1

• Degree (BEng, MSc and PhD) from a top university in a field, such as: Mathematics, Computer Science, Physics, Electrical engineering or equivalent
• High GPA and academic grades
• Research mentality: deep thinker, creative, strong work ethic, persevering, smart & a self-starter
• Programming skills – C++ and Python predominantly, but newer skills welcomed too
• Strong interest in learning about worldwide financial markets
• Strong communication skills in English – including both written and verbal

• While not required, a strong interest in financial markets will definitely be beneficial. Prior experience in quant research will count as a big plus
• Strong record of research achievement – examples include scientific publications, conference presentations, grants or industry awards

The Role: Research is at the core of WorldQuant. Through rigorous exploration and unconstrained thinking about how to apply data to the financial markets, our researchers are in constant search of new alphas. Researchers at WorldQuant employ tested processes seeking to identify high-quality predictive signals that we believe are undiscovered by the wider market. These signals are mathematical expressions of data that are used as inputs in our quantitative models.

WorldQuant is seeking an exceptional individual to join the firm as a Quantitative Researcher focusing on Quant Macro signals research. The person must have a strong understanding of the investment research process to create computer-based models that seek to predict movements of global financial markets, specialized in futures contracts or Macro asset classes – Commodities, FX, Interest Rates, or Equity Indices. While prior finance experience is not required, a successful candidate must possess a strong interest in learning about finance and global markets. Candidates will have a research scientist mind-set; be a self-starter, a creative and persevering deep thinker who is motivated by unsolved challenges.

What You’ll Bring:

• Degree (BEng, MSc and PhD) from a top university in a field, such as: Mathematics, Computer Science, Physics, Electrical engineering, Financial Engineering that is highly analytical or equivalent
• Expertise in the typical quantitative research toolkit: data processing, modeling, and visualization in python, R, or C++
• Experience with futures contracts or Macro asset classes – Commodities, FX, Interest Rates, or Equity Indices–is not required, but is a significant plus.
• High GPA and academic grades
• Research mentality: deep thinker, creative, strong work ethic, persevering, smart & a self-starter
• Strong interest in learning about worldwide financial markets
• Strong communication skills in English

• Strong record of research achievement – examples include scientific publications, conference presentations, grants or industry awards

• Have a Master’s degree or higher from a leading university in Computer Science, Electrical Engineering or other related areas
• Good academic record
• Familiar with modeling, data structures, algorithms and optimizations
• Strong knowledge of machine/deep learning algorithms
• Proficient in programming languages of both C++ and Python
• Possess good communication and presentation skills in English
• Ability to work independently and as member of a team
• Research scientist mindset: deep thinker, creative, strong work ethic, persevering, smart & a self-starter
• Detail oriented and capable of multitasking and delivering in fast-paced work environment

• While not mandatory, a strong interest in financial markets will definitely be beneficial
• Participant of ACM-ICPC

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 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

We are looking for a Senior Machine Learning Scientist to join the Enterprise Solution Science Team.
Our team focuses on applying cutting-edge ML technologies to real-world marketing problems by combining them with omnichannel customer data.
In this role, you will be responsible for end-to-end development, from problem definition to driving model deployment into production.

What You’ll Work On

• Work on one or more of the following topics: user intention prediction, user segmentation, product recommendation, campaign content optimization, and send time optimization.
• Collaborate with product teams to translate product goals and business needs into well-defined ML problems during the planning stage.
• Work closely with ML engineers to deploy models to production, ensuring reliability and maintainability.
• Conduct offline and online evaluation, monitoring, and continuous optimization of models after deployment.
• Stay up to date with the latest research and proactively propose innovative applications.
• Mentor junior scientists and help evolve team developing culture and standards.

What We’re Looking For (Minimum)

• Master’s or PhD degree in Computer Science, Machine Learning, Mathematics, Electrical Engineering, or related fields.
• 3+ years of experience applying ML techniques in areas such as prediction, optimization, segmentation, or recommendation.
• Proficient in Python and commonly used ML frameworks such as PyTorch or TensorFlow.
• Practical experience in deploying enterprise-grade ML models, including model pipeline and performance dashboard development.
• Experience in cross-functional collaboration and leading industry projects.
• Strong sense of impact, with excellent analytical and problem-solving skills, and a passion for new technologies.
• Proficient in using LLM-powered tools (e.g., Github Copilot, ChatGPT) to boost development productivity.

What We’re Looking For (Preferred)

• Industry experience in the MarTech domain, with a strong passion for building customer-centric products.

#LI-AK1

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

We are looking for a Senior Machine Learning Scientist, LLM to join the Enterprise Solution Science Team. 
This team focuses on applying cutting-edge ML technologies to real-world marketing problems by combining them with omnichannel customer data.
In this role, you will be responsible for end-to-end development, from problem definition to driving model deployment into production.

What You’ll Work On

• Work on one or more of the following LLM-related topics: agents, chatbots, copilots, RAG systems
• Collaborate with product teams to translate product goals and business needs into well-defined ML problems during the planning stage
• Work closely with ML engineers to deploy models to production, ensuring reliability and maintainability
• Conduct offline and online evaluation, monitoring, and continuous optimization of models after deployment
• Stay up to date with the latest research and proactively propose innovative applications
• (Optional) Mentor junior scientists and help evolve team developing culture and standards.

What We’re Looking For (Minimum)

• Master’s or PhD degree in Computer Science, Machine Learning, Mathematics, Electrical Engineering, or related fields
• 3+ years of experience in machine learning or engineering roles
• Experience in building and deploying enterprise-level LLM applications (e.g., intelligent agents)
• Familiar with LLM evaluation techniques, including hallucination detection and confidence scoring, with an emphasis on quantitative metrics and systematic benchmarking.
• Hands-on experience with multi-step reasoning, modular workflows (e.g., multi-component prompting, agent orchestration), and RAG pipelines
• Experience in cross-functional collaboration and leading industry projects 
• Strong sense of impact, with excellent analytical and problem-solving skills, and a passion for new technologies
• Proficient in using LLM-powered tools (e.g., Github Copilot, ChatGPT) to boost development productivity

What We’re Looking For (Preferred)

• Industry experience in the MarTech domain, with a strong passion for building customer-centric products
• Experience with LLM toolkits or frameworks like LangChain, AutoGen, or Google ADK
• Familiarity with prototyping tools such as Streamlit or Gradio
• Knowledge of fine-tuning or adaptation techniques, such as LoRA or instruction tuning

#LI-AK1

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 Machine Learning Scientist in Appier, you will be contributing to Appier’s research in actual use case for our products.

Responsibilities

• Use machine learning and analytical techniques to build prediction model for advertising/enterprise solutions.
• Experience in analyzing and extracting valuable information from large amounts of business data
• Design, develop and test advanced models for predictive consumer behavior
• Co-operate with software engineering teams to drive real-time model implementations and new feature creations
• Design efficient, scalable, automated processes for large scale data analyses, model development, model validation and model implementation
• Research and evaluate pioneering machine learning and statistical model

About you

[Minimum qualifications]

• Master or Ph.D. in Computer Science, Machine Learning, Math or Statistics. (Familiar with probabilistic model predictive models)
• Solid experience in system design and programming, ability to work with big data with minimal engineering support
• 3+ year experience in data mining, algorithms, statistical analysis, computational NLP and/or machine learning
• Proven ability of solving challenging problems in both academia and industry
• Extensive publication experience
• Self-motivation and an ability to priorities multiple competing challenges in a fast-growth environment
• Thinking about thinking; meta-cognition
• Applying past knowledge to new situations; remain open to continuous learning
• Thinking and communicating with clarity and precision

[Preferred qualifications]

• Excellent presentation skill to articulate product ideas to technical/non-technical audience

#LI-AK1