Machine Learning Engineer

About the role

We are looking for a Machine Learning Engineer to join our Advanced Computing team. This position focuses on developing predictive models and optimization strategies that enhance our open finance platform. You will take ownership of the entire process, from research and experimentation to deployment and monitoring.

Key facts

What you'll do

• Develop and maintain models for time-series forecasting, optimizing client portfolios, and predicting deal complexity.
• Design and implement a conversational interface for financial advisors to access predictions and insights.
• Create optimization strategies to improve cash management and resource allocation across diverse client portfolios.
• Monitor model performance and ensure continuous improvement through automated retraining and versioning.

Requirements

• At least 3 years of experience in time-series forecasting using techniques like ARIMA, LSTM, or Prophet, with proven accuracy in real-world applications.
• Proficiency in constrained optimization methods, such as linear programming or genetic algorithms, applied to financial contexts.
• Experience with end-to-end ML operationalization, including CI/CD for model deployment and monitoring.
• Familiarity with AWS ML tools, including SageMaker, Lambda, DynamoDB, and S3.
• Competence in containerization technologies like Docker and Kubernetes for scalable deployments.
• Strong programming skills in Python, with experience in libraries such as pandas, numpy, and TensorFlow or PyTorch.

Nice to have

• Background in financial services, particularly in wealth management or liquidity management.
• Experience with real-time systems and low-latency prediction APIs.
• Knowledge of natural language processing and document processing, especially with AWS tools.
• Familiarity with advanced optimization techniques, including quantum computing methods.

Skills & tools

• Time-series forecasting techniques (ARIMA, LSTM, Prophet)
• Optimization algorithms (linear programming, genetic algorithms)
• AWS ML stack (SageMaker, Lambda, DynamoDB, S3)
• Containerization (Docker, Kubernetes)
• Python libraries (pandas, numpy, TensorFlow, PyTorch)

Practical notes

• The salary range for this position is between $175,000 and $200,000.
• Candidates should be eligible to work in the United States.
• Applications will be accepted until the position is filled.