Lead Machine Learning Engineer
Tasks
- Build ML platform in GCP
- Deploy and monitor machine learning models
- Design machine learning pipelines
- Develop MLOps frameworks and SDKs
- Develop reusable ML components
- Evaluate emerging ML systems generative AI and agents
- Implement metadata tracking feature versioning model governance
- Integrate CI CD for ML workflows
- Mentor and lead machine learning engineers
- Optimize data processing and orchestration
- Orchestrate training and evaluation pipelines
- Review architecture and code for engineering standards
Perks/Benefits
- Dental cover
- Employee wellbeing programme
- Enhanced parental leave
- Hybrid work
- Learning budget
- Pension match
- Private medical insurance
- Study leave
- Travel season ticket loan
Skills/Tech-stack
AI Pipelines | BigQuery | CI/CD | Cloud Build | Cloud Composer | Cloud Run | Docker | Drift Detection | Feature versioning | GCP | GitHub Actions | IAM | Infrastructure as Code | MLOps | Machine Learning | Metadata tracking | Model Drift | Model Drift Detection | Model Governance | Model Monitoring | Model Registry | Neural Networks | Pub/Sub | PyTorch | Python | Reproducibility | Rollback strategies | Terraform | Vertex AI | Vertex AI pipelines | “as-code”
Education
Associate Degree | Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
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