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We are seeking a Senior Machine Learning Engineer with a strong trading and financial services background to design and deploy machine learning solutions supporting trading and investment platforms. This role requires deep expertise in machine learning engineering, data analysis, and production-grade ML systems. The ideal candidate will be responsible for developing ML models, building the infrastructure required for training and deployment, and working directly with business stakeholders to deliver impactful data-driven solutions within trading environments.
Job Responsibility:
Design, develop, and deploy machine learning models and ML-powered applications
Build infrastructure and tooling for training, deploying, and monitoring ML models
Perform feature engineering, data processing, and large-scale data analysis
Convert ML prototypes into scalable production systems
Collaborate directly with trading teams, business stakeholders, and engineering teams
Implement best practices for model performance, monitoring, and scalability
Develop solutions that support equity or fixed income trading use cases
Ensure ML systems are robust, efficient, and production-ready
Requirements:
Strong programming experience with Python, Java, or other ML-related languages
Strong understanding of Machine Learning algorithms and techniques
Experience working with ML frameworks such as TensorFlow, PyTorch, Scikit-learn
Strong experience in data handling, feature engineering, and data analysis
Experience building infrastructure for training, deploying, and monitoring ML models
Ability to convert research prototypes into production-grade ML systems
Experience working in Financial Services, particularly trading environments
Hands-on experience supporting Equity or Fixed Income trading use cases
Strong communication skills with the ability to work independently and collaborate with business stakeholders
Nice to have:
Experience working with large-scale financial datasets
Exposure to real-time trading systems or market data platforms
Strong understanding of ML system architecture and production pipelines