Senior Machine Learning Engineer
About the role
The Senior Machine Learning Engineer is responsible for building, deploying, and maintaining scalable AI/ML solutions within the bank. This role bridges data science and software engineering, focusing on developing reliable MLOps pipelines, moving models into production, and ensuring their performance, security, and compliance with regulatory standards. The engineer will collaborate with data scientists, architects, and IT operations to integrate ML models into legacy systems and digital channels, optimize model inference, and manage infrastructure on cloud platforms, primarily Google Cloud Platform. The position also involves mentoring junior engineers and maintaining thorough documentation for audit readiness.
Must have
- Bachelor's or Master's degree in Computer Science, Data Science, Software Engineering, Mathematics, or a related field recognized by the University Grants Commission.
- 4+ Years of total experience in software engineering, data engineering, or machine learning.
- 3+ Years of hands-on experience as a Machine Learning Engineer, specifically focusing on model deployment and MLOps.
- Proven track record of deploying and managing ML models in a complex enterprise environment (Banking/Telco/Insurance is highly preferred).
- Core Languages: Expert proficiency in Python and SQL.
- ML Frameworks and Algorithms: Deep knowledge of machine learning algorithms, libraries and frameworks (e.g., scikit-learn, TensorFlow, PyTorch, XGBoost).
- Cloud & MLOps: Experience with Google Cloud Platform (GCP), Vertex Al, BigQuery, and Dataflow. Proficiency in MLOps tools (e.g., MLflow, Kubeflow) and CI/CD pipelines.
- Infrastructure: Experience with containerization and orchestration (Docker, Kubernetes, Cloud Run) and API development (REST/gRPC, FastAPI/Flask).
- Engineering Pragmatism: Focuses on building scalable, reliable, and secure solutions rather than just experimenting with the latest algorithms. Prefers robust configurations.
- Problem Solver: Ability to troubleshoot complex integration and performance issues across hybrid architectures (connecting Cloud services to On- Premise/Legacy systems).
- Collaborative Leader: Excellent communication skills with the ability to mentor junior engineers and effectively translate technical ML concepts to cross- functional stakeholders.
- Ownership: Takes end-to-end responsibility for models in production, from release to retirement.
Nice to have
- Familiarity with Java/Spring Boot (the standard for our banking backends) is a strong plus.
Technologies
- BigQuery
- CI/CD
- Data Engineering
- Data Science
- Docker
- FastAPI
- Feature Engineering
- Flask
- GCP
- gRPC
- Java
- Kubeflow
- Kubernetes
- Machine Learning
- Microservices
- MLflow
- MLOps
- Model Deployment
- Python
- PyTorch
- scikit-learn
- Spring / Spring Boot
- SQL
- TensorFlow
- Test Automation
- XGBoost
Highlights
ORYSYS Limited is an equal opportunity employer. All recruitment decisions are based solely on suitability, and applications are processed in accordance with the company's privacy policy. Experience in banking, telco, or insurance environments is highly preferred.
Jobs across Sri Lanka, watched for you.Colombo, Sri Lanka