Job Description
As a core member of the company's technical team, the candidate will be responsible for driving innovation in algorithm model research and development. This includes leading end-to-end processes from data preprocessing and feature engineering to the technical implementation of rule-based algorithms. The role requires deep involvement in building scalable algorithm architectures and developing cutting-edge models using both machine learning and deep learning frameworks. These models will be strategically applied to solve complex business problems and enhance product performance. Additionally, the candidate will independently support the algorithm development lifecycle for business products, ensuring seamless integration with front-end development and testing teams. Collaboration will involve participating in comprehensive R&D activities such as data cleaning, algorithm design, performance optimization, deployment, and user feedback tracking. The position demands a proactive approach to identifying technical challenges and proposing data-driven solutions to improve product outcomes.
Key Responsibilities
- Lead algorithm model research and development projects, focusing on data preprocessing, feature engineering, and rule-based algorithm implementation
- Design and build scalable algorithm architectures for diverse business applications
- Develop and deploy machine learning and deep learning models to optimize business processes
- Collaborate cross-functionally with front-end product development and testing teams to ensure algorithm integration
- Execute comprehensive data cleaning and preprocessing workflows
- Participate in algorithm design and implementation for product development
- Implement performance optimization techniques to enhance model efficiency
- Oversee deployment processes and monitor system performance post-implementation
- Track user feedback to identify areas for algorithm improvement and refinement
- Conduct technical analysis to align algorithm solutions with business objectives
- Document algorithm workflows and maintain technical specifications for team reference
- Stay updated with emerging algorithm technologies and industry best practices
- Coordinate with stakeholders to define requirements for algorithm development
- Perform iterative testing and validation of algorithm models
- Develop prototype solutions for new business scenarios
- Collaborate on data governance strategies for algorithm training
- Implement automated monitoring systems for algorithm performance
- Conduct root cause analysis for model failures or inefficiencies
- Develop documentation for algorithm deployment and maintenance
- Participate in technical reviews to ensure algorithm quality and compliance
Job Requirements
- Master's degree or higher in Computer Science, Mathematics, or related fields
- 5+ years of hands-on experience in algorithm development and machine learning
- Proven expertise in deep learning frameworks such as TensorFlow or PyTorch
- Strong background in data preprocessing techniques and feature engineering
- Experience with building scalable algorithm architectures for enterprise applications
- Excellent understanding of performance optimization and deployment strategies
- Proficiency in programming languages including Python, R, and SQL
- Ability to collaborate effectively with cross-functional teams
- Strong analytical skills with experience in data-driven decision making
- Experience with cloud platforms for algorithm deployment (AWS, Azure, GCP)
- Knowledge of CI/CD pipelines for model development and testing
- Excellent communication skills for presenting technical findings to non-technical stakeholders
- Ability to document complex algorithm workflows and technical specifications
- Experience with version control systems (Git) for code management
- Strong problem-solving skills with a track record of innovative solutions
- Knowledge of data governance and ethical AI practices
- Experience with real-time data processing and streaming algorithms
- Ability to work independently while maintaining team collaboration
- Proficiency in using algorithm evaluation metrics (accuracy, precision, recall)
- Experience with model monitoring and maintenance in production environments
