What Jobs are available for Predictive Analytics in Hong Kong?

Responsibility:

• Develop, train and deploy artificial intelligence and machine learning models to solve complex business challenges;
• Responsible for various data preprocessing activities including collection, cleansing and validation of large datasets, and transforming the data into format suitable for consumption by artificial intelligence and machine learning models;
• Conduct in-depth data analysis on large datasets, and apply statistical and machine learning algorithms for extracting meaning from data and identifying actionable insights;
• Continuously monitor model performance and iterate to improve performance and efficiency of models with a view to optimizing business function;
• Responsible for preparation and maintenance of documentations in relation to the model development throughout the model development lifecycle;
• Assist in building a compliance data warehouse and continuously expanding data scope according to the need of AML monitoring, optimizing database performance and improving data usage experience;
• Assist in management and maintenance of the compliance data warehouse, including formulating database management policy and procedure, developing and maintaining data dictionary, monitoring data quality and ensuring data security;
• Assist in data management within the department, including data accountability management, data governance, data quality and security, etc.;
• Collaborate closely with cross-functional teams and external parties including business stakeholders, inhouse IT and data scientist team and solution vendors;
• Research emerging artificial intelligence trends and models, and integrate the new techniques to enhance model capabilities

Requirements:

• Bachelor degree or above in Computer Science, Data Science, Financial Mathematics, Statistics, Finance, Economics, or related disciplines
• 3-5 years or above relevant experience in implementation of artificial intelligence and machine learning models; experience in Banking data management, analysis and application being an advantage (For Senior Manager, at least 8 years relevant experience)
• Proficiency in programming languages, including Python and R, and machine learning libraries
• Strong understanding of machine learning algorithms, deep learning and statistical methods
• Strong problem-solving ability with passion for analytic excellence, able to manage complex scenario challenges simultaneously and work independently and under pressure
• Experience in financial service industry or financial crime compliance domain, or possession of relevant qualification in CAMS, ECF (AML/CFT) Core Level, FRM, CPA, ACCA being an advantage
• Good command of written and spoken English and Chinese

Responsibility:

• Develop, train and deploy artificial intelligence and machine learning models to solve complex business challenges;
• Responsible for various data preprocessing activities including collection, cleansing and validation of large datasets, and transforming the data into format suitable for consumption by artificial intelligence and machine learning models;
• Conduct in-depth data analysis on large datasets, and apply statistical and machine learning algorithms for extracting meaning from data and identifying actionable insights;
• Continuously monitor model performance and iterate to improve performance and efficiency of models with a view to optimizing business function;
• Responsible for preparation and maintenance of documentations in relation to the model development throughout the model development lifecycle;
• Assist in building a compliance data warehouse and continuously expanding data scope according to the need of AML monitoring, optimizing database performance and improving data usage experience;
• Assist in management and maintenance of the compliance data warehouse, including formulating database management policy and procedure, developing and maintaining data dictionary, monitoring data quality and ensuring data security;
• Assist in data management within the department, including data accountability management, data governance, data quality and security, etc.;
• Collaborate closely with cross-functional teams and external parties including business stakeholders, inhouse IT and data scientist team and solution vendors;
• Research emerging artificial intelligence trends and models, and integrate the new techniques to enhance model capabilities

• Bachelor degree or above in Computer Science, Data Science, Financial Mathematics, Statistics, Finance, Economics, or related disciplines
• 3-5 years or above relevant experience in implementation of artificial intelligence and machine learning models; experience in Banking data management, analysis and application being an advantage (For Senior Manager, at least 8 years relevant experience)
• Proficiency in programming languages, including Python and R, and machine learning libraries
• Strong understanding of machine learning algorithms, deep learning and statistical methods
• Strong problem-solving ability with passion for analytic excellence, able to manage complex scenario challenges simultaneously and work independently and under pressure
• Experience in financial service industry or financial crime compliance domain, or possession of relevant qualification in CAMS, ECF (AML/CFT) Core Level, FRM, CPA, ACCA being an advantage
• Good command of written and spoken English and Chinese

Transform Language Models into Real-World Applications
We're building AI systems for a global audience. We are living in an era of AI transition - this new project team will be focusing on building applications to enable more real world impact and highest usage for the world.

This role is a global role with hybrid work arrangement - combining flexible remote work with in-office collaboration at our HQ. You'll work closely with regional teams across product, engineering, operations, infrastructure and data to build and scale impactful AI solutions.

Why This Role Matters
You'll fine-tune state-of-the-art models, design evaluation frameworks, and bring AI features into production. Your work ensures our models are not only intelligent, but also safe, trustworthy, and impactful at scale.

What You'll Do

• Fine-tune & adapt - Use LoRA/QLoRA to optimize open-source models (LLaMA, Mistral, Gemma)
• Engineer prompts & curates data - Craft prompts and datasets that reflect tone, brand voice, and safety.
• Evaluate models – Build metrics pipelines for perplexity, toxicity, and relevance to ensure safe and high-quality outputs.
• Deploy & monitor – Scale models into production with performance optimization and monitoring for drift.
• Collaborate & deliver – Partner with product, engineering, and design teams to launch user-facing AI features.

What Is It Like

• Likes ownership and independence
• Believe clarity comes from action - prototype, test, and iterate without waiting for perfect plans.
• Stay calm and effective in startup chaos - shifting priorities and building from zero doesn't faze you.
• Bias for speed - you believe it's better to deliver something valuable now than a perfect version much later.
• See feedback and failure as part of growth - you're here to level up.
• Possess humility, hunger, and hustle, and lift others up as you go.

Requirements

• Strong experience in transformers, deep learning, and fine-tuning methods (LoRA/QLoRA, SFT, distillation).
• Proficiency with PyTorch (preferred) or TensorFlow.
• Skilled in prompt engineering and dataset curation for alignment with tone, safety, and trust.
• Familiar with evaluation metrics: perplexity, toxicity, relevance.
• Strong software engineering foundations in algorithms, data structures, and clean code practices.

Nice to Have

• Prior work in text generation, moderation, or personalization.
• Experience with RLHF or reinforcement learning in LLMs.
• Contributions to open-source ML projects.

What You'll Get

• Flat structure & real ownership
• Full involvement in direction and consensus decision making
• Flexibility in work arrangement
• High-impact role with visibility across product, data, and engineering
• Top-of-market compensation and performance-based bonuses
• Global exposure to product development
• Lots of perks - housing rental subsidies, a quality company cafeteria, and overtime meals
• Health, dental & vision insurance
• Global travel insurance (for you & your dependents)
• Unlimited, flexible time off

Our Team & Culture
We're a densed, high-performance team focused on high quality work and global impact. We behave like owners. We value speed, clarity, and relentless ownership. If you're hungry to grow and care deeply about excellence, join us.

About Bjak
BJAK is Southeast Asia's #1 insurance aggregator with 8M+ users, fully owned by its employees. Headquartered in Malaysia and operating in Thailand, Taiwan, and Japan, we help millions of users access transparent and affordable financial protection through We simplify complex financial products through cutting-edge technologies, including APIs, automation, and AI, to build the next generation of intelligent financial systems.

If you're excited to build real-world AI systems and grow fast in a high-impact environment, we'd love to hear from you.

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

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