Principal Machine Learning Engineer
Tasks
- Architect ML platform
- Build ML and generative AI systems
- Build scalable training and inference infrastructure
- Create developer abstractions for model deployment
- Design production hosting for AI models
- Evaluate and adopt modern AI technologies
- Implement MLOps experiment tracking
- Implement model versioning
- Implement monitoring and governance
- Lead ML platform engineering
- Partner with AI researchers and data scientists
- Provide technical leadership and design review
- Set up CI CD for ML
Perks/Benefits
- N/A
Skills/Tech-stack
APIs | Agentic AI | CI/CD | Cloud Native | Cloud Native Architecture | Databricks | Distributed Systems | Event Driven | Event-driven architecture | Experiment tracking | Fine Tuning | Generative AI | Governance | LLM Fine-tuning | Language Models | Large Language Models | MLOps | MLflow | Machine Learning | Model Serving | Model versioning | Monitoring | Python | Retrieval-Augmented Generation | Vector Databases
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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