As a Software Developer Intern at Optiver, you’ll work alongside experienced engineers to develop innovative solutions that enable us to respond to the financial markets at lightning-fast speeds. In just a few weeks, you could develop applications that contribute towards our trading success.

By the end of the 8-week internship, you’ll have deepened your understanding of how technology is used in the quantitative trading industry. Plus, if you’ve excelled over the summer, you’ll receive an offer to return as a Graduate Software Developer.

WHAT YOU’LL DO:

Led by our in-house education team that consists of ex-traders and engineers, you’ll delve into advanced engineering concepts and lead innovative projects, during our world-class training program.

In just a few weeks, you'll have the opportunity to manage a project from end-to-end, learn how to work with a complex code base and make impactful contributions to production systems. You’ll get to work on real trading and IT problems, both technically and functionally, to improve our trading success.

You will also be able to build the compute platform and libraries for large scale machine learning model training and simulation workloads. You will have first-hand experience on applying the latest AI technology to quantitative trading problems.

Throughout the program, you will be paired with an experienced mentor, who will show you the ins-and-outs of our trading systems and provide you with guidance and feedback. Additionally, internal resources will be available for your continuous learning and development.

WHAT YOU’LL GET:

You’ll join a culture of collaboration and excellence, where you’ll be surrounded by curious thinkers and creative problem solvers. Driven by a passion for continuous improvement, you’ll thrive in a supportive, high-performing environment alongside talented colleagues, working collectively to tackle the most complex problems in the financial markets.

In addition, you’ll receive:

• A highly competitive remuneration package.

• Optiver-covered flights and accommodation for the duration of the internship.

• The opportunity to work alongside best-in-class professionals.

• Training, mentorship and personal development opportunities.

• Gym membership, plus weekly in-house chair massages.

• Daily breakfast, lunch and in-house barista.

• Regular social events.

WHO YOU ARE:

• Students who are graduating in 2027 or after 2026 September.

• Studying a Computer Science, Computer/Software/Electrical/Mechatronic Engineering or similarly technical degree.

• Knowledgeable about object orientated design and development concepts (experience with C++, C#, Python or Java is required for our technical assessment). 

• Understanding of the concepts underlying machine learning and deep learning technologies, and experience with modern deep learning frameworks such as TensorFlow, PyTorch etc

• Natural problem solvers who love nothing more than tackling a complex technical challenge.

• Team players who love working with like-minded peers and are always looking to learn and improve.

• Interested in the trading/quantitative finance industry (previous knowledge is not required).

HOW TO APPLY:

If you're ready to take the next step in your career and work on one of the most exciting trading floors in mainland China, we’d love to hear from you. Apply now via the form below. Applications close 16 March 2026.

In your application, please submit the following materials in English:

• Resume

• Cover letter (optional)

For any other inquiries, contact us at chinacareers@optiver.com.au

DIVERSITY STATEMENT

Optiver is committed to diversity and inclusion. We encourage applications from candidates of all backgrounds, and welcome requests for reasonable adjustments during the process.

We accept one application per role per year. If you have previously applied to this position during this season and have been unsuccessful, you can re-apply when the next recruitment season begins in 2027.

PRIVACY DISCLAIMER

Optiver 重视个人信息的保护。请您在提供个人信息给我们之前，认真阅读Optiver China Privacy Notice, 了解我们如何收集及处理您的个人信息。

Personal information protection is of utmost importance to Optiver. Before you provide any personal information to us, we strongly urge you to read our Privacy Policy to acknowledge how we collect and process your personal information.

Key Skills & Requirements:

• Core Technical
• Strong Python proficiency — you'll refactor research code into robust, tested production pipelines daily
• Awareness of performance and optimisation — profiling, memory management, and computational efficiency when scaling research code across large universes
• Solid software engineering practices: version control, unit testing, code review, CI/CD, and refactoring — you care about code quality, not just code that works
• Comfortable on Linux platforms with working knowledge of shell scripting
• Experience with data analysis libraries (NumPy, SciPy, pandas) and handling large datasets
• Familiarity with databases and data infrastructure (SQL, data pipelines, or tools like ArcticDB)
• Exposure to ML/DL frameworks (PyTorch, TensorFlow, scikit-learn) or LLM-related tooling
• Research & Domain
• Relevant mathematical knowledge — statistics, optimisation, or factor modeling — enough to understand the research you're productionising
• A keen interest in financial markets and how quantitative strategies are built and deployed
• Nice-to-Haves
• Prior internship in quantitative development, systematic investing, or front-office technology
• Education
• Currently enrolled at a top-tier university in Computer Science, Software Engineering, Mathematics, Physics, or a related field with strong computational content

Key Skills & Experience:

• Core Technical
• Strong Python proficiency — you'll use it daily for signal research, backtesting, data processing, and prototyping
• Solid foundation in quantitative methods: statistics, probability, optimization, and factor modeling
• Hands-on experience with ML/DL (PyTorch, TensorFlow, or similar) — not just coursework, but building and validating models end-to-end
• Practical exposure to LLMs and AI agents — whether prompt engineering, fine-tuning, or building LLM-powered research workflows
• Research & Domain
• Exposure to factor-based strategies, portfolio construction, or systematic alpha research — able to independently design, test, and critically evaluate signals with rigour
• Comfortable working with new or unstructured datasets — cleaning, exploring, and extracting value from imperfect data
• Ability to assist PMs with portfolio analytics — analysing return attribution, risk decomposition, and testing portfolio construction parameters
• Nice-to-Haves
• Prior internship in quantitative research or systematic investing
• Familiarity with China equity markets (A-shares, market structure)
• Versatility to move between research and engineering — equally comfortable exploring a novel idea and shipping high-quality code
• Education
• Currently enrolled at a top-tier university in Computer Science, Mathematics, Statistics, Physics, or a related quantitative field

Senior Staff/Staff Machine Learning Engineer-LLM

Company Introduction

We exist to wow our customers. We know we’re doing the right thing when we hear our customers say, “How did we ever live without Coupang?” Born out of an obsession to make shopping, eating, and living easier than ever, we are collectively disrupting the multi-billion-dollar commerce industry from the ground up and establishing an unparalleled reputation for being leading and reliable force in South Korean commerce.

We are proud to have the best of both worlds — a startup culture with the resources of a large global public company. This fuels us to continue our growth and launch new services at the sped we have been at since our inception. We are all entrepreneurial surrounded by opportunities to drive new initiatives and innovations. At our core, we are bold and ambitious people that like to get our hands dirty and make a hands-on impact. At Coupang, you will see yourself, your colleagues, your team, and the company grow every day.

Our mission to build the future of commerce is real. We push the boundaries of what’s possible to solve problems and break traditional tradeoffs. Join Coupang now to create an epic experience in this always-on, high-tech, and hyper-connected world.

Summary:

At Coupang, we invest in providing the best product experience for our customers. The AI and Knowledge Engineering team’s mission is to provide the best possible technical solution to achieve the optimal experience for our customers. We innovate and advance the space of Knowledge Graphs, agents, LLMs, AI, ML, NLP, and multi-modal models. We are looking for engineers who want to work on cutting edge technology, that is the intersection of Semantic knowledge bases, agents, NLP, LLM, ML and software engineering. Come join us to help create a world class team advancing the AI/NLP/ML/LLM/RL/Knowledge Graph technologies.

The Role/Responsibilities:

• Work on GenAI, self-learning systems to solve complex eCommerce scenarios.
• Develop statistical models for predictive and compound AI Models
• Train foundational models that can help with building learning systems.
• Define process and experiments for an E2E foundation model.
• Build E2E AI pipelines for storing/servicing foundational models.
• Mentor and guide team members on frameworks, methodologies related to data lakes, data normalization, dimension reduction, visualization, statistical models.
• Ensure Model training is security, compliance aware.
• Collaborate with cross-team members to understand the requirements ensuring the foundational models, knowledge captured aligns with the company’s overall AI strategy.

What you will bring/ Requirements:

• Overall 10+ years of working in software engineering and AI/ML Engineering.
• 4+ years of demonstrated data science, experience in building large scale foundational models for eCommerce scenarios.
• Expertise in large language model fine-tuning and deployment.
• Deep understanding of AI/ML/Deep-learning and statistical model architecture.
• Strong statistical/mathematical background in defining metrics, learning functions and result analysis.
• Significant experience in SQL, Python, PySpark, Scala and R
• Proficiency in PyTorch/TensorFlow, Spark, BigQuery
• Experience in creating complex data visualization tools, frameworks and techniques.
• Experience in dimension reduction in big data.
• Proficient in cloud analytical stacks [ Lakes, warehouse, ETL pipelines]
• Experience with inference platforms in AWS, Azure and other open-source platforms.
• Are result-oriented, with a bias towards customer obsession, flexibility, and impact.
• Strong written and verbal communication and teamwork skills
• Passion for Large language models, NLP, and Machine Learning at scale

Education: B.S, M.S in Computer science or Mathematics, or related field

Recruitment Process

Application Review - Phone Interview - Onsite (or Virtual Onsite) Interview – Offer

The exact nature of the recruitment process may vary according to the specific job and may be changed due to scheduling or other circumstances.

Interview schedules and the results will be informed to the applicant via the e-mail address submitted at the application stage.

Details to Consider

This job posting may be closed prior to the stated end date for application if all openings are filled.

Coupang has the right to rescind an offer of employment if a candidate is found to have submitted false information as part of the application process.

Those eligible for employment protection (recipients of veteran’s benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws.

Privacy Notice​

Your personal information will be collected and managed by Coupang as stated in the Application Privacy Notice located below: https://taou.cn/zlO8

[Applied in Coupang.Jobs] Equal Opportunities for All

Coupang is an equal opportunity employer. Our unprecedented success could not be possible without the valuable inputs of our globally diverse team.

Equal Opportunities for All

Coupang is an equal opportunity employer. Our unprecedented success could not be possible without the valuable inputs of our globally diverse team

Senior Staff/Staff Machine Learning Engineer-LLM

Company Introduction

We exist to wow our customers. We know we’re doing the right thing when we hear our customers say, “How did we ever live without Coupang?” Born out of an obsession to make shopping, eating, and living easier than ever, we are collectively disrupting the multi-billion-dollar commerce industry from the ground up and establishing an unparalleled reputation for being leading and reliable force in South Korean commerce.

We are proud to have the best of both worlds — a startup culture with the resources of a large global public company. This fuels us to continue our growth and launch new services at the sped we have been at since our inception. We are all entrepreneurial surrounded by opportunities to drive new initiatives and innovations. At our core, we are bold and ambitious people that like to get our hands dirty and make a hands-on impact. At Coupang, you will see yourself, your colleagues, your team, and the company grow every day.

Our mission to build the future of commerce is real. We push the boundaries of what’s possible to solve problems and break traditional tradeoffs. Join Coupang now to create an epic experience in this always-on, high-tech, and hyper-connected world.

Summary:

At Coupang, we invest in providing the best product experience for our customers. The AI and Knowledge Engineering team’s mission is to provide the best possible technical solution to achieve the optimal experience for our customers. We innovate and advance the space of Knowledge Graphs, agents, LLMs, AI, ML, NLP, and multi-modal models. We are looking for engineers who want to work on cutting edge technology, that is the intersection of Semantic knowledge bases, agents, NLP, LLM, ML and software engineering. Come join us to help create a world class team advancing the AI/NLP/ML/LLM/RL/Knowledge Graph technologies.

The Role/Responsibilities:

• Work on GenAI, self-learning systems to solve complex eCommerce scenarios.
• Develop statistical models for predictive and compound AI Models
• Train foundational models that can help with building learning systems.
• Define process and experiments for an E2E foundation model.
• Build E2E AI pipelines for storing/servicing foundational models.
• Mentor and guide team members on frameworks, methodologies related to data lakes, data normalization, dimension reduction, visualization, statistical models.
• Ensure Model training is security, compliance aware.
• Collaborate with cross-team members to understand the requirements ensuring the foundational models, knowledge captured aligns with the company’s overall AI strategy.

What you will bring/ Requirements:

• Overall 10+ years of working in software engineering and AI/ML Engineering.
• 4+ years of demonstrated data science, experience in building large scale foundational models for eCommerce scenarios.
• Expertise in large language model fine-tuning and deployment.
• Deep understanding of AI/ML/Deep-learning and statistical model architecture.
• Strong statistical/mathematical background in defining metrics, learning functions and result analysis.
• Significant experience in SQL, Python, PySpark, Scala and R
• Proficiency in PyTorch/TensorFlow, Spark, BigQuery
• Experience in creating complex data visualization tools, frameworks and techniques.
• Experience in dimension reduction in big data.
• Proficient in cloud analytical stacks [ Lakes, warehouse, ETL pipelines]
• Experience with inference platforms in AWS, Azure and other open-source platforms.
• Are result-oriented, with a bias towards customer obsession, flexibility, and impact.
• Strong written and verbal communication and teamwork skills
• Passion for Large language models, NLP, and Machine Learning at scale

Education: B.S, M.S in Computer science or Mathematics, or related field

Recruitment Process

Application Review - Phone Interview - Onsite (or Virtual Onsite) Interview – Offer

The exact nature of the recruitment process may vary according to the specific job and may be changed due to scheduling or other circumstances.

Interview schedules and the results will be informed to the applicant via the e-mail address submitted at the application stage.

Details to Consider

This job posting may be closed prior to the stated end date for application if all openings are filled.

Coupang has the right to rescind an offer of employment if a candidate is found to have submitted false information as part of the application process.

Those eligible for employment protection (recipients of veteran’s benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws.

Privacy Notice​

Your personal information will be collected and managed by Coupang as stated in the Application Privacy Notice located below: https://taou.cn/zlO8

[Applied in Coupang.Jobs] Equal Opportunities for All

Coupang is an equal opportunity employer. Our unprecedented success could not be possible without the valuable inputs of our globally diverse team.

WHO WE ARE LOOKING FOR:

At The Trade Desk, the Data Science team is responsible for transforming our hundreds of terabytes of Real-Time Bidding (RTB) advertising auction data into actionable intelligence, using advanced modelling and optimization algorithms. Our mission is to develop new and powerful means of growing the value of our client’s campaigns across millions of web-based publishers. Our team believes in innovation that contributes to our product. In this role, you will be a key member in the development of entirely new data products and the improvement of existing ones, all while using world-class machine learning. You will interact primarily with our product, trading, and engineering teams to oversee the implementation of your data products. Your ideas and research will contribute directly to our client facing product.

WHAT YOU WILL BE DOING:

• Be an intellectually generous and collaborative team member
• Develop end-to-end machine learning prototypes that could scale to run in a production environment
• Contribute meaningful improvements to existing machine learning models through carefully directed research
• Maintain a focus on shipping product, understanding that oftentimes done is better than perfect
• Derive actionable insights from massive data sets with minimal support
• Provide input into the collection of new data sources and the refinement of existing ones to improve analysis and model development
• Become an expert on TTD’s client-facing platform

WHAT YOU BRING TO THE TABLE:

NON-TECHNICAL QUALIFICATIONS:

• You are enthusiastic to learn (and teach) new technologies, machine learning techniques, and advancements in the adtech industry
• You are comfortable working on an agile, distributed team spanning multiple time zones and continents
• You have an abundance of intellectual curiosity
• You are able to deliver a convincing story derived from the data sets to both a technical and non-technical audiences
• You have experience working closely with engineering team to bring ideas into real product
• Experience in digital advertising and/or recommendation system, relevant experience in recall / ranking is a plus

TECHNICAL QUALIFICATIONS:

• A relevant scientific and mathematical education (Masters and/or PhD welcome) with 5+ years of professional or academic experience in a data driven role working with massive data sets
• You have a solid understanding of statistical machine learning and optimization techniques as well as the ability to derive actionable insights from massive data sets
• You have experience recall/matching/retrieval algorithms
• You have experience in Adtech or recommendation systems
• You are familiar with one of the deep learning frameworks (e.g., Tensorflow, Pytorch, MXNet), knowledge of inference optimization is a plus
• You have experience with big data technologies such as Spark, AWS, Hadoop, Hive and are able to write efficient SQL
• You have experience in multiple programming languages (Python, R, Scala, Java, etc.) and are fluent at some selections of those

The Trade Desk does not accept unsolicited resumes from search firm recruiters. Fees will not be paid in the event a candidate submitted by a recruiter without an agreement in place is hired; such resumes will be deemed the sole property of The Trade Desk. The Trade Desk is an equal opportunity employer. All aspects of employment will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.

About Us

AXQ Capital is a global quantitative investment firm with offices in New York, Beijing, Shanghai, and Hong Kong. We pursue consistent alpha through rigorous scientific research and sustained investment in technology and data infrastructure. Our strategies are deployed across global markets, spanning multiple geographies, asset classes, and trading horizons.

Job Duties 

As a Machine Learning Researcher, you will develop ML/DL models to generate alpha from large-scale financial and alternative datasets. Working closely with portfolio managers and senior quantitative researchers, you will conduct research across a range of trading strategies within a fast, iterative research-feedback loop.

Qualifications

Below is a list of skills and experiences we believe are relevant. Even if you don’t consider yourself a perfect match, we still encourage you to apply because we are committed to helping our people grow and develop.

• Master’s or PhD from a top-tier university in a quantitative discipline (e.g., mathematics, physics, statistics, computer science, or related fields)
• Strong foundation in machine learning, statistics, and optimization, with deep expertise in at least one area such as time series modeling, NLP, or LLMs
• Strong communication skills and ability to collaborate effectively in a research-driven environment
• Experience with the Python scientific and ML ecosystem (e.g., NumPy, Pandas/Polars, PyTorch, TensorFlow)
• Proven ability to build and improve models that perform under noisy, non-stationary, and high-dimensional data conditions
• Intellectually curious, highly analytical, and driven to discover alpha in complex systems
• Self-motivated and highly productive, with strong ownership and a bias toward action
• Publications at top-tier venues such as NeurIPS, ICML, KDD, or IJCAI
• Strong track record in competitive ML platforms (e.g., Kaggle) or academic competitions
• Prior experience in quantitative research, systematic trading, or alpha signal generation

Department：Avatar

职位：制造大模型算法工程师（Downstream）

职责描述：

1. 与资深制造大模型算法工程师合作，开发基于多模态电池基础大模型的下游应用。
2. 参与开发和优化多个具体应用模型，包括电芯质量评估模型、生产过程优化模型、电芯设计优化模型、电芯性能预测模型以及电芯设计生成式模型。
3. 协助实施和优化数据处理管道，确保数据准确性和一致性，以支持下游应用开发。
4. 应用机器学习和深度学习技术进行模型训练、验证和优化。
5. 分析和处理复杂的数据集，提取关键特征以改进模型性能和应用效果。
6. 协助跨职能团队理解业务需求并制定相应的技术实现方案。
7. 持续跟踪最新技术发展，协助引入前沿方法提升模型应用效果。

任职资格：

1. 计算机科学、电子工程、统计学或相关领域的硕士学位。
2. 至少3年以上在机器学习或AI领域的实际工作经验，有制造业或电池生产相关经验者优先。
3. 熟悉机器学习和深度学习算法，具备多模态数据处理与应用开发经验者优先。
4. 熟练掌握Python、TensorFlow、PyTorch等常用的机器学习框架和工具。
5. 具备处理表格数据、时序数据和图像数据的能力，并能够将这些数据应用于具体的模型开发。
6. 良好的沟通能力和团队协作精神，能有效与跨职能团队合作。
7. 具备良好的问题解决能力和学习新技术的意愿。

Responsibilities:

1. Cooperate with senior AI/ML engineers to develop downstream applications based on multi-mode battery basic large model.
2. Participate in the development and optimization of multiple specific application models, including cell quality assessment model, production process optimization model, cell design optimization model, cell performance prediction model and cell design generative model.
3. Assist in implementing and optimizing data processing pipelines to ensure data accuracy and consistency to support downstream application development.
4. Apply machine learning and deep learning technology for model training, verification and optimization.
5. Analyze and process complex data sets, extract key features to improve model performance and application effect.
6. Assist cross-functional teams to understand business requirements and develop corresponding technical implementation plans.
7. Continue to track the latest technological development and help introduce cutting-edge methods to improve the application effect of the model.

Qualifications:

1. Master's degree in computer science, electrical engineering, statistics or related field.
2. At least 3 years of practical working experience in machine learning or AI field, manufacturing or battery production experience is preferred.
3. Familiar with machine learning and deep learning algorithms, multi-modal data processing and application development experience is preferred.
4. Proficient in Python, TensorFlow, PyTorch and other commonly used machine learning frameworks and tools.
5. Have the ability to process tabular data, time series data and image data, and can apply these data to specific model development.
6. Good communication skills and team spirit, able to effectively work with cross-functional teams.
7. Good problem-solving skills and willingness to learn new technologies.

Jump Trading Group is committed to world class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incentivizing collaboration and mutual respect. At Jump, research outcomes drive more than superior risk adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.

Our trading teams are each comprised of a dynamic group of traders, quantitative researchers, and engineers who work together to examine the global markets, seeking to understand the complexities of various traded products and exchanges. They leverage their impeccable statistical analysis and data mining skills, using the results of their research to make forecasts and develop profitable predictive trading models.

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*Candidates should be interested in working in Asia for their full-time job after graduation.

*INTERNATIONAL STUDENTS are encouraged to apply. 
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Who Should Apply?

• We are seeking researchers with a demonstrated ability to apply machine learning to achieve state-of-the-art capabilities in complex and challenging domains. 
• The ideal person for this role will be capable of implementing an open-ended research project from concept to production and continuously improving model design, tools, and infrastructure. 
• Potential projects may target any area of the quantitative research and monetization process. We believe that successful research efforts require a fluid mix of skills including ML expertise, engineering pragmatism, statistics and market intuition.
• No prior knowledge of finance or trading is necessary. We’ll give you the training that you’ll need.
  
• Other duties as assigned or needed.

Skills You'll Need: 

• Creative thinkers who are driven, self-motivated, and eager to solve challenging problems with a pragmatic outlook
• Strong publication record at ICML, ICLR, AAAI, NeurIPS, UAI, KDD, or equivalent and/or contributions to open-source AI research
• Familiarity with ML libraries/frameworks such as PyTorch, TensorFlow, and/or JAX
• Proficiency in Python and/or C++
• Ability to thrive in a collaborative, team-oriented environment
• Ability to reason through quantitative problems and communicate effectively with trading researchers
• Strong general ML background with exposure to modern deep learning techniques and/or language modeling architectures (e.g. transformers, SSMs)
• Reliable and predictable availability required

If you have outstanding skills in math, ML, and programming, and you are curious about the challenge of improving research with daily feedback from competitive markets, we hope you’ll apply.