Senior ML Engineer

Senior ML Engineer - 12 Month Contract

Key Responsibilities

• Design, develop, and deploy ML models in AWS SageMaker and EKS.

• Optimize ML models for real-time decisioning in high-traffic environments.

• Ensure models comply with regulatory and security standards.

• Build and maintain CI/CD pipelines for ML model deployments.

• Automate model retraining, monitoring, and logging using AWS Lambda, Terraform, and Control-M jobs.

• Implement observability tools like OpenSearch, FluentBit, Prometheus, Kibana, Grafana, and AWS CloudWatch.

• Develop ETL/ELT pipelines for data preprocessing and feature engineering.

• Work with AWS Redshift to process large-scale datasets for model training.

• Monitor ML models running 24/7 in production, ensuring reliability and high availability.

• Work closely with engineering teams to troubleshoot and optimize production systems.

• Participate in an on-call rotation for urgent ML pipeline issues.

• Collaborate with data scientists, decision engineers, and credit engineers to align ML solutions with business needs.

• Take ownership of ML solutions and provide guidance to junior engineers.

• Contribute to the ongoing AI/ML strategy within the business.

Required Skills & Qualifications:

Technical Skills:

• 5+ years of experience in Machine Learning Engineering.

• Strong expertise in Python, PySpark, SQL, and ML libraries (TensorFlow, PyTorch, Scikit-learn).

• Experience with AWS ML services (Amazon SageMaker, EKS, Lambda, Redshift, Control-M, Terraform).

• Experience with MLOps practices (CI/CD pipelines with GitHub Actions, Docker, Kubernetes).

• Proficiency in observability & monitoring tools: OpenSearch, FluentBit, Kibana, Prometheus, Grafana, CloudWatch.

• Strong understanding of real-time ML applications in financial environments.

• Experience in building and maintaining ETL pipelines in a cloud environment.

Soft Skills:

• Leadership & Ownership Ability to work independently and drive ML initiatives.

• Problem-Solving Ability to troubleshoot ML model failures in production.

• Strong Communication Work effectively with cross-functional teams.

• Agility Adapt to a fast-paced, high-stakes environment.

• Banking Industry Experience Preferred.