MLOps Engineer
Tasks
- Build and scale machine learning capabilities
- Build data pipelines and analytics services
- Build event-driven architectures
- Build scalable backend services
- Deploy and serve machine learning models
- Design distributed systems
- Design machine learning platform
- Develop microservices
- Implement Feature Stores
- Implement model registries
- Improve platform performance
- Own systems end-to-end
- Use Docker and Kubernetes for cloud deployments
Perks/Benefits
- Collaborative work environment
- International customer exposure
- Mentorship programs
- Professional development opportunities
Skills/Tech-stack
Distributed Systems | Docker | Elasticsearch | Event Driven | Event-driven architecture | FastAPI | Hugging Face | Kubernetes | Microservices | NumPy | Pandas | PostgreSQL | PyTorch | Python | Relational databases | Scikit-learn | TensorFlow
Education
Bachelor of Arts | Bachelor of Engineering | Bachelor of Science
Regions
Countries
States
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