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Senior Engineer - Data Science
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Oct 1, 2026, 12:17 AM3w ago
ContractColombo, Western ProvinceData scienceSenior (3+ yrs)
About the role
The Senior Engineer - Data Science role focuses on developing and deploying production-grade machine learning, deep learning, and generative AI solutions. The position involves building and optimizing ML models, implementing MLOps and LLMOps pipelines, integrating AI into enterprise applications, and ensuring scalable, reliable, and production-ready AI systems. Key responsibilities include model development, deployment, monitoring, collaboration with platform teams, technical documentation, and mentoring junior staff. The ideal candidate will have strong experience in Python, ML/DL libraries, cloud platforms, MLOps tools, and a solid understanding of data pipelines and AI integration in enterprise contexts.
Must have
- Bachelor's degree in IT/Computer Science, Data Science, Engineering, Mathematics, or a related field
- 03+ years of hands-on experience in data science or machine learning engineering roles
- Strong experience with Python and common ML/DL libraries (scikit-learn, PyTorch, TensorFlow, NumPy, pandas)
- Proven experience developing and deploying production-grade ML models
- Hands-on experience with MLOps platforms and tools (e.g., MLflow, Kubeflow, SageMaker, Vertex AI, or equivalent)
- Practical exposure to LLMOps, including prompt engineering, fine-tuning, evaluation, and model serving
- Experience working with APIs, microservices, and integrating ML models into enterprise applications
- Solid understanding of data pipelines, feature engineering, and model lifecycle management
- Experience with cloud platforms (AWS, Azure, or GCP) and containerization (Docker, Kubernetes)
- Experience applying AIOps techniques in monitoring, observability, or IT/network operations contexts
- Knowledge of time-series analysis, anomaly detection, or large-scale telemetry data
- Familiarity with vector databases, RAG pipelines, and embedding models
- Exposure to API management platforms and security concepts (authentication, rate limiting, governance)
- Experience with CI/CD pipelines for ML and AI systems
- Prior experience in telecommunications, fintech, or large-scale enterprise environments
- Strong analytical and problem-solving skills with a pragmatic, engineering-first mindset
- Ability to communicate complex technical concepts clearly to both technical and non-technical stakeholders
- Comfortable working in cross-functional, agile teams
- Self-driven, accountable, and capable of owning solutions end-to-end
- Passion for continuous learning and applying emerging AI technologies responsibly
Technologies
- Agile
- Anomaly Detection
- Authentication
- AWS
- Azure
- CI/CD
- Data Engineering
- Data Pipelines
- Data Science
- Deep Learning
- Docker
- Feature Engineering
- Fine-Tuning
- Fintech
- GCP
- Generative AI
- Kubeflow
- Kubernetes
- LLM
- LLMOps
- Machine Learning
- Microservices
- MLflow
- MLOps
- NumPy
- Observability
- pandas
- Prompt Engineering
- Python
- PyTorch
- RAG
- SageMaker
- scikit-learn
- TensorFlow
- Time Series
- Vector Databases
- Vertex AI
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