200 Machine Learning jobs in Hong Kong

Overview

R&D in machine learning for speech and language technologies. Assist in designing and implementing machine learning models for speech recognition, natural language processing (NLP), and voice applications. Support data preprocessing, feature engineering, and model training on multi-lingual datasets. Location: Kwun Tong, Hong Kong SAR.

• R&D in machine learning for speech and language technologies
• Assist in designing and implementing machine learning models for speech recognition, NLP, and voice applications
• Support data preprocessing, feature engineering, and model training on multi-lingual datasets
• Document work and stay updated on advances in speech and language technologies

• Bachelor’s degree in Computer Science, Electrical Engineering, or related field
• Preferably 1–2 years of working experience as a Machine Learning Engineer; fresh graduates will also be considered
• Strong math/statistics foundation and problem-solving skills
• Good communication and teamwork abilities

• Entry level

• Full-time

• Engineering and Information Technology

• Staffing and Recruiting

Referrals increase your chances of interviewing at Peoplebank. Get notified about new Machine Learning Engineer jobs in Kwun Tong, Hong Kong SAR.

Direct message the job poster from AAA Global

Industry: Quantitative Research / Artificial Intelligence

Experience: Mid to Senior Level (Academic or Industry Research)

Employment Terms: Full-time

Compensation: $150,000–$50,000 USD

The Role – Machine Learning Researcher

A leading quantitative research group is seeking exceptional machine learning researchers to join their growing team. You will collaborate with experienced ML scientists and quant researchers to apply cutting-edge ML techniques to unique, proprietary datasets and develop high-impact trading signals.

This is a rare opportunity to work on research that leads directly to real-world results — no prior experience in finance is required.

Responsibilities And Priorities:

• Own the full lifecycle of ML research projects — from ideation and implementation to validation and deployment

• Adapt and extend existing models across ML fields to uncover predictive patterns in noisy, high-dimensional datasets

• Explore novel approaches to enhance portfolio performance and prediction capabilities

• Stay current with developments in AI/ML and bring new tools and ideas into the research workflow

• Collaborate with a highly technical and experienced team in a low-ego, results-oriented environment

Requirements:

• Master’s or PhD in machine learning, computer science, statistics, or a related discipline

• Prior experience conducting ML research with large, imperfect datasets

• Strong proficiency in Python and ML libraries such as Torch, JAX, or TensorFlow

• Understanding of modern sequence models, graph neural networks, reinforcement learning, or LLMs

• Familiarity with cluster computing environments and software engineering best practices (e.g., source control, testing)

• Strong analytical and quantitative skills; able to approach complex problems methodically

• Excellent written and verbal communication skills

• Team player with a collaborative mindset and high ethical standards

The Profile – Your Expertise

We're looking for inventive, self-directed researchers who are excited by the application of machine learning to real-world problems. You’ll thrive in this role if you enjoy taking ownership of ideas and developing them rigorously — with the space, resources, and data to see your work deliver real impact.

Experience, Ability And Knowledge:

• Demonstrated success in ML research (academic, open source, or industry)

• Ability to independently drive research projects

• Depth in one or more ML domains (e.g., generative models, graph-based ML, deep learning, RL)

• An appreciation for reproducibility, clarity, and collaborative workflows

Who You Are, What We Need:

• A clear thinker with strong written and verbal communication skills

• Self-motivated and comfortable in a highly technical peer group

• Open-minded and pragmatic when testing ideas and choosing methods

• Committed to the highest standards of professional conduct

The Package

• Annual base salary range: $150,000–$250,000 USD

• Discretionary bonus compens tion

• High-impact role with autonomy and ownership

• Access to one of the most interesting ML datasets in the space

• Seniority level Mid-Senior level

• Employment type Full-time

• Job function Finance

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Job description

Job Description:

As a Machine Learning Engineer at TeamNote, you will be instrumental in developing and optimizing a private GPT application designed for deployment within a corporate environment. You will work closely with a talented team to build and enhance the machine learning components of the application, ensuring high performance, accuracy, and scalability.

Responsibilities:

• Develop and train machine learning models, particularly focusing on natural language processing (NLP) for the private GPT application.
• Collaborate with software engineers to integrate machine learning models, Retrieval-Augmented Generation (RAG) pipelines and LLM agents into the application infrastructure.
• Optimize and fine-tune the GPT model and inferencing backend for specific corporate use cases and requirements.
• Conduct experiments, analyze data, and iterate on model performance to enhance overall application capabilities.
• Implement best practices for model deployment, monitoring, and maintenance within a corporate setting.
• Stay updated on the latest advancements in machine learning and Large Language Model (LLM) to drive innovation within the project.

Qualifications:

• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field (Master's degree or PhD preferred).
• Proven experience in machine learning, deep learning, and NLP, with a strong portfolio of projects demonstrating expertise in these areas.
• Proficiency in machine learning frameworks such as TensorFlow, PyTorch, MLX or similar tools.
• Solid programming skills in languages like Python, with experience in data manipulation, analysis, and visualization.
• Strong understanding of statistical modelling and algorithms used in machine learning.
• Familiarity with Retrieval-Augmented Generation (RAG) and LLM agent frameworks is considered a strong advantage.
• Experience in Large Language Model (LLM) inferencing backend such as vLLM, SGLang, or MLX is highly desirable.
• Excellent problem-solving abilities, analytical skills, and attention to detail.
• Effective communication skills and the ability to collaborate with cross-functional teams.

Additional Information:

• This is a full-time position based in Hong Kong.
• Competitive salary and benefits package.
• Opportunity to work on cutting-edge AI technologies and contribute to the development of innovative solutions within a corporate environment.

If you are passionate about machine learning, eager to work on AI-driven applications, and thrive in a collaborative team setting, we would love to hear from you.

工作類型: 全職

薪酬: $15,000.00至$25,000.00(每月)

福利:

• 在家工作
• 有薪病假
• 彈性上班時間
• 醫療保險

Work Location: 親身到場

The Role:

• R&D in machine learning for speech and language technologies
• Assist in designing and implementing machine learning models for speech recognition, natural language processing (NLP), and voice applications
• Support data preprocessing, feature engineering, and model training on multi-lingual datasets
• Document work and stay updated on advances in speech and language technologies

Experience Needed:

• Bachelor's degree in Computer Science, Electrical Engineering, or related field.
• Perferably 1-2 years of working experience as Machine Learning Engineer, Fresh graduates will also be considered
• Strong math/statistics foundation and problem-solving skills
• Good communication and teamwork abilities

The Role

• R&D in machine learning for speech and language technologies
• Assist in designing and implementing machine learning models for speech recognition, natural language processing (NLP), and voice applications
• Support data preprocessing, feature engineering, and model training on multi-lingual datasets
• Document work and stay updated on advances in speech and language technologies

Experience Needed

• Bachelor's degree in Computer Science, Electrical Engineering, or related field.
• Perferably 1-2 years of working experience as Machine Learning Engineer, Fresh graduates will also be considered
• Strong math/statistics foundation and problem-solving skills
• Good communication and teamwork abilities

Job Responsibilities

• Conduct data analysis, feature engineering, and feature extraction for data within the financial industry
• Develop and implement cutting-edge machine learning algorithms focused on graph learning and time series analysis for applications such as transaction monitoring, anti-money laundering, and cryptocurrency analysis
• Maintain and optimize data pipelines, enhancing existing solutions through pre- and post-processing improvements, fine-tuning, performance evaluation, visualization, and testing
• Collaborate with cross-functional teams to identify and address customer needs and aspirations
• Proactively resolve ambiguity and tackle technical issues, driving innovation and efficiency in processes

Job Requirements

• Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, Statistics, or related fields
• Proficiency in at least one machine learning development framework, such as PyTorch, Keras, or TensorFlow, with hands-on experience in environment control
• Experience with programming, monitoring, visualization and project collaboration tools, including Python, VSCode, Conda, Git, and MySQL
• Knowledge of statistical machine learning and deep learning, particularly the models for graph and/or time series data, such as knowledge graph, spatial-temporal graph, and multivariate time series
• Interest in areas such as anomaly detection, federated learning, transfer learning, self-supervised learning, or uncertainty quantification
• Knowledge in LLM is a plus
• A passion for coding, programming, innovation, and problem-solving
• A keen interest in anti-money laundering practices and regulatory compliance
• Proficient in written and spoken Chinese (Cantonese or Mandarin); fluency in English is a plus

About the Position

Machine learning is a critical pillar of Jane Street's global business, and our ever-changing trading environment serves as a unique, rapid-feedback platform for ML experimentation.

Researchers at Jane Street are responsible for building models, strategies, and systems that price and trade a variety of financial instruments. As a mix of the trading and software engineering roles, this work involves many things: analyzing large datasets, building and testing models, creating new trading strategies, and writing the code that implements them.

We're looking for people to join the research team with deep ML experience in either an applied or academic context. A good candidate should have a deep understanding of a wide variety of ML techniques, and a passion for tinkering with model architectures, feature transformations, and hyperparameters to generate robust inferences. We also want people who are good communicators, with the ability to quickly absorb the context of a new problem, carefully consider tradeoffs, and recommend possible solutions.

As an ML researcher, your expertise will also shape the firm's future ML developments including hiring new ML researchers, attending conferences, teaching techniques to teammates, and setting firmwide goals.

If you're a recruiting agency and want to partner with us, please reach out to agency-

Lyodssoft Limited is seeking self-motivated team member to build AI capabilities for financial institutions across AML transaction monitoring, KYC, and anti-fraud, improving compliance efficiency and risk controls. You can obtain the great opportunity to develop careers in AI and Big Data for different business applications.

Responsibilities:

• Responsible for technical research and development of a distributed AI platform.
• Translate business problems into measurable AI tasks and deliver the end-to-end lifecycle: data → features → training → evaluation → deployment → monitoring.
• Establish baselines and KPIs for key use cases (e.g., Precision/Recall/F1, MAE/MAE, latency, QPS, alert reduction, manual review time).
• Responsible for communicating to AI Team Leader and Technical Director for overall R&D project management.

Qualifications:

• Master's degree in computer science, Mathematics or a related discipline with 3-5 years relevant experience for Senior position
• Master's degree or equivalent in Computer Science, Mathematics or a related discipline or bachelor's degree with at least one-year relevant experience for Trainee position.
• Familiar with AI expertise, including Machine Learning, Deep Learning, Natural Language Processing, Large Language Models, etc.
• Proficient in Python and common libraries (Numpy, Pandas, etc.); familiar with PyTorch/TensorFlow and scikit-learn; at least one database (MySQL, MSSQL, Oracle); at least one web framework (FastAPI/Flask).
• Bonus: LangChain/Dify, vector DBs (FAISS/Milvus/Pinecone); Docker/K8s experience
• Good analytical and independent/team problem-solving skills
• Have good communication and collaboration skills: fluent in at least two of Cantonese, English and Mandarin.
• IANG/overseas applicants welcome

What we offer:

• Frontline FinTech/RegTech projects in partnership with compliance teams at financial institutions across multiple regions.
• High ownership in a small team with a clear career path and a dedicated learning and development budget.
• Competitive salary commensurate with your skills and experience.

Machine Learning Researcher

Location:
Hong Kong

Industry:
Quantitative Research / Artificial Intelligence

Experience:
Mid to Senior Level (Academic or Industry Research)

Employment Terms:
Full-time

Compensation:
$150,000–$50,000 USD

The Role – Machine Learning Researcher

A leading quantitative research group is seeking exceptional machine learning researchers to join their growing team. You will collaborate with experienced ML scientists and quant researchers to apply cutting-edge ML techniques to unique, proprietary datasets and develop high-impact trading signals.

This is a rare opportunity to work on research that leads directly to real-world results — no prior experience in finance is required.

Responsibilities And Priorities:

• Own the full lifecycle of ML research projects — from ideation and implementation to validation and deployment

• Adapt and extend existing models across ML fields to uncover predictive patterns in noisy, high-dimensional datasets

• Explore novel approaches to enhance portfolio performance and prediction capabilities

• Stay current with developments in AI/ML and bring new tools and ideas into the research workflow

• Collaborate with a highly technical and experienced team in a low-ego, results-oriented environment

Requirements:

• Master's or PhD in machine learning, computer science, statistics, or a related discipline

• Prior experience conducting ML research with large, imperfect datasets

• Strong proficiency in Python and ML libraries such as Torch, JAX, or TensorFlow

• Understanding of modern sequence models, graph neural networks, reinforcement learning, or LLMs

• Familiarity with cluster computing environments and software engineering best practices (e.g., source control, testing)

• Strong analytical and quantitative skills; able to approach complex problems methodically

• Excellent written and verbal communication skills

• Team player with a collaborative mindset and high ethical standards

The Profile – Your Expertise

We're looking for inventive, self-directed researchers who are excited by the application of machine learning to real-world problems. You'll thrive in this role if you enjoy taking ownership of ideas and developing them rigorously — with the space, resources, and data to see your work deliver real impact.

Experience, Ability And Knowledge:

• Demonstrated success in ML research (academic, open source, or industry)

• Ability to independently drive research projects

• Depth in one or more ML domains (e.g., generative models, graph-based ML, deep learning, RL)

• An appreciation for reproducibility, clarity, and collaborative workflows

Who You Are, What We Need:

• A clear thinker with strong written and verbal communication skills

• Self-motivated and comfortable in a highly technical peer group

• Open-minded and pragmatic when testing ideas and choosing methods

• Committed to the highest standards of professional conduct

The Package

• Annual base salary range: $150,000–$250,000 USD

• Discretionary bonus compensation

• Comprehensive benefits package

• High-impact role with autonomy and ownership

• Access to one of the most interesting ML datasets in the space