Machine Learning Engineer
Tasks
- Build serverless ML architectures using infrastructure as code
- Create ML APIs with authentication and async processing
- Design batch processing pipelines for ML inference
- Develop LLM solutions using cloud services
- Develop model monitoring dashboards and visualizations
- Document technical solutions and communicate with stakeholders
- Implement LLM output validation and error detection
- Implement model context protocol servers for tool integration
- Optimize LLM costs and evaluation metrics
- Translate business requirements into ML solutions
Perks/Benefits
- Company social insurance coverage
- Company team events
- Flexible-hybrid work
- Free lunch
- Holiday gifts
- Private health insurance
- Vacation 15 days per year
Skills/Tech-stack
AWS Bedrock | AWS CDK | AWS Lambda | Access Control | Amazon Fargate | Asynchronous programming | Azure OpenAI | Batch Processing | CI/CD | Docker | ETL | FastAPI | FastAPI authentication | Git | Google Gemini | Hyperparameter Tuning | IAM | JSON Web Token | Model Evaluation | NumPy | Okta | Pandas | Prompt engineering | Python | SQL | Scikit-learn
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Regions
Countries
States
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