ML/AI Engineer
Tasks
- Build RAG-architectures
- Build inference pipelines
- Build training pipelines
- Build validation pipelines
- Collaborate with data engineers
- Collaborate with developers
- Contribute to engineering best practices
- Create embeddings
- Design machine learning models
- Ensure model reliability
- Ensure privacy & compliance
- Ensure responsible AI compliance
- Ensure security compliance
- Implement CI/CD for ML workflows
- Implement deployment and rollback
- Implement generative AI models
- Manage model versioning
- Mentor junior engineers
- Monitor model bias
- Monitor model drift
- Monitor model performance
- Optimize compute usage
- Optimize inference performance
- Optimize latency
- Optimize operational costs
- Perform feature engineering
Perks/Benefits
- Cumulative vacation
- Employer retirement plan contribution
- Flexible working hours
- Health insurance
- Parking reimbursement
- Personal days
- Professional development allowance
- Public transportation reimbursement
- Referral bonuses
- Social events
- Statutory Holidays
- Training
Skills/Tech-stack
AWS | Amazon SageMaker | Bias monitoring | CI/CD | Compute Optimization | Data Pipelines | Drift monitoring | Embeddings | Feature Engineering | Generative AI | Inference Optimization | Language Processing | Latency optimization | Lifecycle Management | Machine Learning | Model Lifecycle | Model Lifecycle Management | Model Monitoring | Model versioning | Natural Language | Natural Language Processing | Performance optimization | Privacy Compliance | PyTorch | Python | RAG | Retrieval-Augmented Generation | Scikit-learn | Security Compliance | TensorFlow
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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