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Associate Engineer/Engineer - Data Science/Artificial Intelligence
ZinCaT Technologylinkedin.com
Oct 5, 2026, 11:42 AM3w ago
Full-timeColombo District, Western ProvinceData scienceJunior (1+ yr)
About the role
This role involves designing, developing, and optimizing machine learning and deep learning models, including classical ML approaches and advanced language models. The position requires building and deploying models using frameworks like TensorFlow or PyTorch, implementing MLOps and LLMOps pipelines, and developing solutions for model monitoring and observability. The engineer will collaborate with various teams to expose ML/AI capabilities as APIs, participate in data preparation and feature engineering, and ensure rigorous model validation and benchmarking. The role also includes mentoring junior team members and staying current with advancements in AI and machine learning.
Must have
- Bachelor's degree in IT/Computer Science, Data Science, Engineering, Mathematics, or a related field
- 01 - 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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