At Silent Eight, we develop our own AI-based products to combat financial crimes that enable things like money laundering, the financing of terrorism, and systemic corruption. We’re a leading RegTech firm working with large international financial institutions such as Standard Chartered Bank and HSBC. Join us and help make the world a safer place!
As a Python Developer, you will create and manage applications that bolster our AML solutions and refine machine learning models to improve product functionality. You will work closely with data scientists to implement these models in production environments and design systems for data integration and quality assurance. Furthermore, you will handle the entire machine learning pipeline, from data preprocessing to model deployment, ensuring that applications are scalable and efficient.
Responsibilities
- Develop and maintain Python-based applications and tools that support our AML solutions
- Implement, optimize, and deploy machine learning models, including large language models, to enhance our product capabilities
- Collaborate with data scientists and cross-functional teams to integrate machine learning models into production systems
- Design and implement data integration, validation, and quality check frameworks
- Work on the entire machine learning pipeline, from data preprocessing to model deployment and monitoring
- Create quick prototypes and present them to customers and internal stakeholders to drive product development
- Analyze and process large-scale structured and unstructured data sets to support machine learning initiatives
- Ensure the robustness, scalability, and efficiency of the developed applications and models
- Provide technical support and troubleshoot issues related to machine learning models and Python applications
- Follow best practices in coding, MLOps, and DataOps
- Assist other teams in delivering proof-of-concept projects
Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
- Strong proficiency in Python programming and related libraries (e.g., Pandas, NumPy, scikit-learn)
- Experience in implementing and deploying machine learning models, including large language models (e.g., GPT, BERT)
- Familiarity with machine learning frameworks such as TensorFlow, PyTorch, and Hugging Face Transformers
- Experience with data preprocessing, feature engineering, and model evaluation techniques
- Proficiency in working with large-scale datasets and SQL
- Knowledge of MLOps practices and tools for continuous integration and deployment of machine learning models
- Experience in designing and implementing data integration and validation frameworks
- Strong problem-solving skills and attention to detail
- Excellent communication skills to collaborate with cross-functional teams and present technical concepts to non-technical stakeholders
- Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and big data technologies