Machine Learning Engineer
Tasks
- Build LLM RAG and agentic AI workflows
- Build end to end ML data and model services
- Design production AI and ML platforms
- Detect model drift and handle incidents
- Develop CI CD pipelines for ML workloads
- Implement monitoring, logging, tracing, alerting
- Perform data validation experimentation training evaluation deployment
- Provision cloud infrastructure with Terraform
- Write production Python code and automation scripts
Perks/Benefits
- Career coaching
- Employee assistance programme
- Flexible working hours
- Hybrid work
- Internal tech communities
- Training opportunities
- Wellbeing apps subscription
Skills/Tech-stack
Argo CD | Azure DevOps | CI/CD | Cloud Build | Cloud Networking | Data Science | Data Validation | Docker | Drift Detection | Experiment tracking | Feature Engineering | Feature Store | Git | GitHub Actions | GitLab CI | Helm | IAM | Kubeflow | Kubernetes | Langchain | Llamaindex | MLOps | MLflow | Machine Learning | Model Evaluation | Model Monitoring | Model Registry | Networking Security | NumPy | Pandas | Prompt engineering | PyTorch | Python | RAG | SQL | Scikit-learn | Secrets management | TensorFlow | Terraform | Vertex AI
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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