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Senior Machine Learning Engineer – ML Platform & Operations
CuSolidlinkedin.com
Nov 6, 2026, 10:15 AM2h ago
Full-timeColombo, Western ProvinceML & AISenior (5+ yrs)
About the role
The Senior Machine Learning Engineer – ML Platform & Operations is responsible for deploying and operating machine learning models and services in production environments. The role involves supporting ML workflows, building and maintaining pipelines, monitoring model and service performance, troubleshooting issues, and collaborating with data science and engineering teams. The ideal candidate will have hands-on experience with deploying ML models, cloud platforms, and monitoring tools, as well as strong problem-solving and communication skills. The position emphasizes reliability, scalability, automation, and continuous improvement in ML operations.
Must have
- 5+ years of experience in machine learning, ML infrastructure, cloud engineering, platform engineering, SRE, or a related field
- Hands-on experience deploying or operating machine learning models in production
- Understanding of model evaluation, inference, versioning, and the ML lifecycle
- Experience with at least one major cloud platform, such as Microsoft Azure or AWS
- Experience with JavaScript/TypeScript is required
- Familiarity with cloud ML services such as Azure Machine Learning or Amazon SageMaker, or equivalent tools
- Familiarity with monitoring tools such as Azure Monitor, Amazon CloudWatch, and Datadog
- Understanding of logging, metrics, tracing, monitoring, and alerting
- Experience with containers, APIs, and deployment pipelines
- Knowledge of infrastructure-as-code tools such as Terraform or platform-specific equivalents
- Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field
- Strong problem-solving, troubleshooting, and debugging skills
- A practical understanding of what it takes to run ML systems reliably in production
- Interest in improving model performance, deployment workflows, and ML operations
- Clear communication and a collaborative approach
- A focus on reliability, scalability, automation, and continuous improvement
- Ability to work effectively in a fast-paced, evolving technology environment
Nice to have
- Familiarity with LLM applications and their evaluation or operational requirements is an advantage
- DevOps experience, especially CI/CD, containers, cloud deployments, and infrastructure automation, is an advantage
- Knowledge of Python or other programming languages is an advantage
Technologies
- A/B Testing
- AWS
- Azure
- CI/CD
- CloudWatch
- Data Science
- Datadog
- DevOps
- Infrastructure as Code
- JavaScript
- LLM
- Machine Learning
- Model Evaluation
- Python
- SageMaker
- Terraform
- TypeScript
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