Python Developer

Python Developer

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