Company Description:
Worthland Consulting Inc. is a premier quality recruitment agency based in Canada that specializes in the Web3 and crypto space. Our mission is to connect the best candidates with the right jobs in these industries. Whether you are looking to hire new staff or find a new job, we are here to help.
Role Description:
We are seeking a Machine Learning Engineer for our client, to work onsite in Shenzhen, China. . This role is focused on building and optimizing advanced machine learning models—particularly in recommendation systems—while designing scalable data pipelines, deploying models to production, and driving innovative research to solve complex real-world challenges.
Key Responsibilities:
- Model Development & Optimization : Build, train, optimize, and deploy cutting-edge ML models, including supervised, unsupervised, deep learning, and reinforcement learning approaches. Emphasize improving recommendation system algorithms to enhance prediction accuracy and system robustness.
- Data Processing & Analysis : Extract, clean, transform, and engineer features from both structured and unstructured data sources, ensuring data quality and variety for complex model training. Design efficient data pipelines and distributed processing systems.
- Model Deployment & Maintenance : Integrate ML models into high-availability production environments with continuous performance monitoring and automated tuning (MLOps).
- Research & Innovation : Stay up to date with the latest ML, deep learning, and recommendation system advancements. Propose innovative solutions tailored to user recommendation flows, combining theoretical insights with practical engineering.
- Documentation & Reporting : Produce comprehensive technical documentation, covering theoretical concepts, experimental designs, results analysis, and engineering practices. Present findings in internal knowledge-sharing sessions and academic or industry forums when relevant.
Required Skills and Qualifications:
- PhD in Computer Science, Artificial Intelligence, Data Science, Statistics, Mathematics, or a related field—or equivalent research experience.
- Significant hands-on research or project experience in machine learning, deep learning, or recommendation systems. Prior publications (e.g., NeurIPS, ICML, CVPR) or granted patents are highly valued.
- Proficiency in Python, R, C++, or Java, with in-depth knowledge of common ML frameworks (TensorFlow, PyTorch, JAX, scikit-learn, etc.).
- Experience handling large-scale data, including SQL/NoSQL databases, data pipeline construction, and distributed processing.
- Solid theoretical understanding of statistical learning, optimization algorithms, and deep learning architectures.
- Familiarity with distributed system architecture, Docker, Kubernetes, and cloud platforms (AWS, Azure, GCP).
- Strong academic writing and technical communication skills for effective collaboration and knowledge sharing.
- Ability to thrive in a fast-paced, research-driven environment, juggling multiple projects and deadlines.
Preferred Qualifications:
- Track record of successful recommendation system deployments in either academia or industry (e.g., significant improvements to user retention or engagement).
- Experience working with social product features (user behavior modeling, content recommendation, etc.).
- Hands-on MLOps practice, including automated model training, validation, deployment, and monitoring.
- Proficiency in cloud-based solutions for large-scale training and deployment, along with cost and performance optimization.
