Senior Machine Learning Engineer
Tasks
- Apply cloud AI services
- Build Retrieval Augmented Generation systems
- Build data and feature pipelines
- Collaborate with data science and analytics teams
- Create agentic workflows
- Deploy AI systems at scale
- Design AI/ML infrastructure
- Develop AI ML platforms and tooling
- Develop reusable components for LLM workflows
- Ensure observability and governance
- Implement embeddings
- Implement prompt orchestration
- Maintain AI lifecycle pipelines
- Monitor models for performance and evaluation
- Productionize AI prototypes into production systems
- Use CI CD testing and code quality practices
- Use orchestration tools for AI workflows
Perks/Benefits
- Company holidays
- Flexible holidays
- Free parking
- Gym membership
- Health insurance
- Hybrid work model
- Meal card
- Mental health benefits
- Paid time off
- Stock options
- Study fund
- Volunteering opportunities
Skills/Tech-stack
AWS Bedrock | Agentic Workflows | Amazon S3 | CI/CD | Data Pipelines | Embeddings | Feature Engineering | Governance | LLM | Lambda | ML Infrastructure | MLOps | Machine Learning | Model Evaluation | Observability | Orchestration | Prompt engineering | Prompt orchestration) | Python | Retrieval-Augmented Generation | SageMaker | System design | Testing
Education
N/A
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