AI / ML Engineer
Tasks
- Collaborate with data scientists on model prototypes
- Deploy machine learning models to production
- Develop AI machine learning pipelines
- Implement MLOps monitoring and model versioning
- Integrate models with cloud platforms and applications
- Optimize model performance latency cost
- Orchestrate machine learning workflows
Perks/Benefits
- Annual budget for home workspace
- Equipment provided
- Flexible work-life balance
- Paid vacation
- Remote work
- Sick days
- Training allowance
- Volunteer day
- Wellness budget
Skills/Tech-stack
AWS | Azure | CI/CD | Cloud deployment | Data Engineering | Docker | ELT | ETL | Generative AI | Git | Google Cloud | Kubeflow | Kubernetes | Language Models | Large Language Models | MLOps | Machine Learning | Model Monitoring | Model versioning | PyTorch | Python | Scikit-learn | TensorFlow
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI/ML Engineer | Engineer | ML Engineer
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