What Jobs are available for Machine Learning in Hong Kong?

Systematic Quant Researcher (Mid-Frequency, Equities, ML/NLP) – Hong Kong or Singapore

A leading global multi-strategy hedge fund ($12B AUM) is looking to add a talented Systematic Quant Researcher to its growing mid-frequency equities team in Hong Kong or Singapore.

This is an opportunity to join a world-class platform and work on cutting-edge ML, NLP, and LLM-driven research, collaborating with senior PMs and data scientists to design and deploy alpha-generating strategies.

Key Responsibilities:

• Research and develop systematic mid-frequency equity strategies using advanced ML techniques
• Apply
  Natural Language Processing (NLP)
  and
  Large Language Models (LLMs)
  for signal generation and feature extraction
• Build, test, and deploy predictive models and alpha signals across global markets
• Collaborate with engineers to bring research to production
• Analyze market microstructure and alternative data sources to identify new opportunities

Requirements:

• 5+ years' experience in
  systematic equities research
  (buy-side or sell-side)
• Proven background in
  machine learning, NLP, or LLM-based modeling
• Strong programming skills in
  Python (C++ a plus)
• Solid understanding of alpha research, portfolio construction, and backtesting
• Master's or PhD in a quantitative discipline (Computer Science, Applied Math, Statistics, or similar)
• Experience in
  mid-frequency
  or
  ML-driven systematic
  strategies

Locations:
Hong Kong or Singapore

Compensation:
Highly competitive, performance-based

If you're passionate about applying ML and NLP to real-world trading and want to join a high-impact global fund, we'd love to hear from you.

Job Title:
Machine Learning Scientist

Salary:
Negotiable (max USD 5,000 monthly)

Work Location:
Full-time Remote (GMT+7)

Open to Taiwan/Hong Kong/China-based candidates.

If you hold a PhD in Bioinformatics, Computational Biology, or Computer Science and want to apply your AI research to real-world medicine innovation, we welcome your application.

Job Overview

We are seeking a
Machine Learning Scientist
to join a global R&D team developing an
AI-driven platform for medicine research and healthcare manufacturing
—with a special focus on cancer therapeutics and production optimization. The role involves designing, training, and scaling state-of-the-art ML models that power next-generation healthcare innovation.

This is a
long-term product
, not a short-term project, to build a strong scientific AI team dedicated to advancing medicine discovery through cutting-edge research and production technologies.

Responsibilities

• Design and maintain end-to-end data pipelines to ingest, clean, augment, and version large-scale molecular and phenotypic datasets.
• Automate high-throughput molecular simulations and extract docking features for downstream modeling.
• Research, prototype, and productionize
  graph neural networks
  and
  transformer-based models
  for molecular property prediction, lead optimization, and virtual screening.
• Develop and integrate
  semi-supervised
  and
  active learning
  workflows to extract insights from limited experimental labels.
• Establish evaluation frameworks and analyze model performance using metrics such as ROC-AUC and enrichment factors.
• Collaborate with chemists, biologists, and engineers to integrate ML solutions into the discovery platform, ensuring scalability and maintainability.
• Communicate research progress, results, and methodologies across cross-functional teams and in external presentations.

Requirements

Must-Have:

• PhD (required) in
  Bioinformatics, Computational Biology, Computer Science, or related fields
  .
• Minimum
  5 years of AI/ML research or engineering experience
  .
• Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, or JAX).
• Hands-on experience with graph libraries (DGL, PyG) and transformer frameworks (HuggingFace).
• Familiarity with cheminformatics (RDKit) and molecular docking tools (AutoDock Vina, Glide).
• Experience in distributed training on multi-GPU or cloud platforms (AWS/GCP).
• Strong English reading comprehension for research papers; speaking level sufficient for team communication.
• Ability to travel to Singapore once per year for research collaboration.

Nice-to-Have:

• Research or work experience at
  BioTuring, Gene Solutions
  , or similar biotech/AI firms.
• PhD obtained abroad (US, Singapore, Australia, or Europe).
• Experience with omics data (RNA-seq, WGS, single-cell) and genomics libraries (Bioconductor, scikit-allel).
• Contributions to open-source ML tools or publications in relevant AI/biotech fields.
• Mentoring or leadership experience in research teams.

Company Overview

We are a biotechnology-focused technology organisation backed by global investors and partners from Singapore. The company applies
Artificial Intelligence to the development and production of new medicines
, particularly cancer-related therapeutics.

The mission is to build a new long-term, world-class
AI R&D team
to design intelligent systems that optimise pharmaceutical research and manufacturing. This is not a short-term project but a strategic product under continuous development, representing a major focus of the company's future roadmap.

Working Time

• Monday to Friday, 9:00 AM – 5:00 PM (lunch break: 12:00 – 1:00 PM).
• Full-time remote within the GMT+7 time zone.

Benefits

• Competitive and negotiable salary.
• Work fully remote with a flexible, research-oriented culture.
• Collaborate directly with scientists and AI experts across Singapore and Vietnam.
• Exposure to international pharmaceutical research and innovation.
• Opportunity to contribute to an AI product with long-term global healthcare impact.

Hiring Process

3 rounds: Initial Interview → Technical Interview → Final Interview.

Join us in building next-generation AI systems that will transform global healthcare.

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: $11,643.27至$33,764.89(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

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

We are looking for a Machine Learning Engineer passionate about Speech & Language AI (NLP & ASR) to build and deploy intelligent education technology. You will work on developing speech recognition and natural language processing models that help learners improve their Mandarin, Cantonese, and English language skills.

Responsibilities

• Design and fine-tune ASR/NLP models (Whisper, ESPnet, Hugging Face Transformers, PyTorch/TensorFlow).
• Develop pronunciation assessment and adaptive feedback systems for language learners.
• Collaborate with engineers and educators to integrate models into mobile/web apps.
• Build multimodal pipelines combining speech and text data.
• Optimize performance for real-time, mobile-first applications.

Requirements

• Degree in Computer Science, Electrical Engineering, or related field.
• 2–5 years' experience in machine learning (with focus on NLP/ASR).
• Strong Python skills and experience with PyTorch/TensorFlow.
• Knowledge of speech recognition frameworks (Whisper, ESPnet, Kaldi).
• Familiarity with React Native or Unity a plus.

Job overview and responsibility

• Design and maintain end‑to‑end data pipelines to ingest, clean, augment, and version large‑scale molecular and phenotypic datasets.

• Automate high‑throughput docking simulations; extract, featurize, and curate docking poses and affinity scores for downstream modeling.

• Research, prototype, and productionize graph neural network and transformer‑based models for molecular property prediction, lead optimization, and virtual screening.

• Develop and integrate semi‑supervised learning and active‑learning workflows to maximize insight from limited experimental labels.

• Establish evaluation frameworks and benchmarks; analyze performance metrics (e.g., ROC‑AUC, enrichment factors) and iterate on model architectures to improve accuracy and robustness.

• Collaborate closely with chemists, biologists, and software engineers to integrate ML solutions into NYB's discovery platform, ensuring reproducibility, scalability (distributed/GPU training), and maintainable codebases.

• Communicate results and methodologies in team meetings, internal reports, and through external publications or conference presentations.

Required skills and experiences

• Education & Research:

• PhD or equivalent postdoctoral experience in Computer Science, Computational Biology, Bioinformatics, or a related discipline, with a strong publication record.

• Technical Expertise:

• At least 5+ Years of Experience in AI/ML

• Proficient in Python and ML frameworks (PyTorch, TensorFlow, or JAX); experience with graph libraries (DGL or PyG) and transformer toolkits (Hugging Face).

• Hands‑on with RDKit (cheminformatics) and molecular docking software (e.g., AutoDock Vina, Glide).

• Familiarity with semi‑supervised techniques (consistency regularization, pseudo‑labeling) and self‑attention architectures.

• Infrastructure & Scale: Experience with cloud platforms (AWS/GCP), containerization (Docker/Kubernetes), and distributed training across multi‑GPU clusters.

• Analytical Foundations: Strong background in statistics, optimization, and experimental design; ability to translate biological questions into ML problems.

• Collaboration & Communication: Excellent written and verbal skills; proven ability to work cross‑functionally in fast‑paced environments.

Preferred skills and experiences

• Contributions to open source ML tools; experience in generative molecular modeling; leadership or mentoring of junior researchers.

• Experience working with genomics or omics projects/data (e.g., RNA-seq, WGS, single-cell), including familiarity with common genomics tools and libraries (Bioconductor, scikit-allel, or similar).

Why Candidate should apply this position

• Competitive salary

• Build a professional network through collaborations with pharmaceutical companies, industry leaders, and academic experts.

• Work on impactful projects that address critical challenges in drug discovery and healthcare.

• We provide a dynamic, fast-paced, and collaborative environment where problem-solving and agility are at the heart of what we do. Along with a competitive salary, we foster a culture that values ambition, confidence, and humility, consistently pushing the boundaries of innovation. If you're excited about working in a young, talented tech company and want to explore the world of AI and pharmaceuticals, we encourage you to apply.

Report to

CTO (in VietNam) and Professors, Experts (in Singapore)

Interview process

3 round: Initial Round, Technical Round, Final Round

Machine Learning Engineer

Key Responsibilities

• Develop and maintain production-grade Python applications with clean architecture and modular code structure.
• Build and deploy RESTful APIs for ML models using frameworks such as FastAPI or Flask.
• Ensure code quality through unit testing, integration testing, and performance validation.
• Optimise systems for readability, maintainability, and runtime performance.
• Implement CI/CD pipelines using GitHub Actions, Jenkins, or Airflow to automate deployment workflows.
• Containerise ML services using Docker and deploy with high-performance tools like Gunicorn.
• Work with structured/tabular data using NumPy, Pandas, and integrate with PostgreSQL, MySQL, or data lake platforms like Spark or Databricks.
• Collaborate with cross-functional teams to support ML projects in domains such as space, logistics, energy, and insurance.
• Contribute to infrastructure monitoring and auto-scaling strategies in Kubernetes environments.

Qualifications

• 4+ years of experience in Python development with a focus on backend and data engineering.
• 2+ years of experience deploying ML models via APIs in production environments.
• Strong understanding of software engineering principles and production-grade code packaging.
• Experience with performance testing, stress testing, and system optimisation.
• Familiarity with orchestration tools such as Kubeflow, Ansible, or Apache Airflow.
• Working knowledge of CI/CD practices and container orchestration.
• Basic understanding of ML principles, model lifecycle, and evaluation techniques like cross-validation.
• Experience implementing monitoring systems using tools like Grafana, ELK Stack, MLflow, or ClearML.
• Exposure to infrastructure components such as databases, file storage, caching systems, and message queues.

If you're interested in this role, please send your latest resume to or contact Cheryl Ng

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-