System Architecture Expert

Talent Pro Recruitment; Hong Kong; On-site; HKD 800,000 - 1,200,000; Full time

Job summary

Talent Pro Recruitment is hiring a Senior AI Expert in Hong Kong to design, develop, and deploy AI and machine learning solutions. This role emphasizes collaboration across teams to lead AI/ML projects that solve key business challenges in financial markets.

The ideal candidate will have a PhD in a relevant field and 3-5+ years of experience in delivering ML solutions in production. Strong programming skills in Python and expertise in advanced models are necessary for this position, along with excellent communication skills.

Qualifications

• 3-5+ years of hands-on experience building and delivering ML/AI systems in production.
• Strong understanding of model validation, backtesting, performance metrics, and model risk concepts.
• Demonstrated expertise in time-series modelling and NLP applied to financial text.

Responsibilities

• Lead end-to-end AI/ML projects from problem formulation to deployment.
• Translate business problems into robust ML solutions.
• Design and implement scalable, production-grade models and pipelines.

Skills

Python programming

Machine Learning frameworks (PyTorch, TensorFlow, JAX, scikit-learn)

Time-series modelling

Deep learning (including transformers)

Natural Language Processing (NLP)

Education

PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, Financial Engineering

Tools

ML engineering tools

Job description

Overview

They are a tier‑one organisation with their AI & Data Science organization partners across businesses to build high‑impact, production‑grade AI systems that improve client outcomes, reduce risk, and drive operational efficiency. They value rigorous engineering, responsible use of AI, and strong collaboration between research, engineering, and business stakeholders.

Role overview

wHiring a Senior AI Expert to design, develop, and deploy advanced AI and machine learning solutions that address critical business challenges across . You will combine deep technical expertise with strong domain knowledge in financial markets to lead end‑to‑end delivery of ML‑driven products, mentor team members, and establish best practices for responsible AI at scale

Key responsibilit

• esLead end-to-end AI/ML projects: problem formulation, data strategy, model development, evaluation, deployment, monitoring, and lifecycle managemen
• t.Translate business problems into robust ML solutions that are explainable, auditable and aligned with regulatory and risk framework
• s.Design and implement scalable, production‑grade models and pipelines using modern ML engineering practices (feature stores, CI/CD, model registries, automated testing
• s.-Develop advanced models — e.g., time‑series forecasting, deep learning (transformers, graph neural networks), probabilistic models, reinforcement learning, anomaly detection, NLP for financial text — tailored to trading, pricing, credit/risk, AML/KYC, or client analytic
• s.Drive model validation, stress testing, performance benchmarking, and model risk management in collaboration with validation, risk and compliance team
• s.Establish and evangelize best practices for responsible AI: fairness, interpretability, robustness, data privacy, and secure model deploymen
• t.Collaborate with product managers, quantitative researchers, software engineers, and data engineers to deliver solutions that meet production SLAs and regulatory requirement
• s.Mentor and upskill junior data scientists and engineers, and contribute to hiring and technical review
• s.Maintain awareness of academic and industry advances; propose and prototype novel approaches where they add business valu
• onsPhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, Financial Engineering, or related fie
• Priority is given to candidates with TTPS for non‑HK citiz
• Should be highly presentable and passionate in understanding different business doma
• ins3-5+ years of hands‑on experience building and delivering ML/AI systems in production; prior experience in financial services strongly preferr
• ed.Strong programming skills in Python; experience with ML frameworks such as PyTorch, TensorFlow, JAX, or scikit‑learn
• rn.Practical experience with ML engineering to
• olsDemonstrated expertise in one or more of: time‑series modelling, deep learning (including transformers), graph ML, probabilistic modelling, reinforcement learning, NLP applied to financial te
• xt.Solid understanding of model validation, backtesting, performance metrics, and model risk concep
• ts.Experience working with large‑scale data (structured, semi‑structured, and text) and designing feature engineering pipelin
• es.Excellent communication skills; ability to explain complex models to technical and non‑technical stakeholde
• rs.Strong collaboration skills and experience working in cross‑functional teams under regulatory constrain