AI/ML Engineer
Tasks
- Apply MLOps practices including CI CD and model monitoring
- Coordinate with data scientists and software engineering teams
- Deploy and scale AI models
- Deploy models to cloud environments
- Develop AI machine learning pipelines
- Implement model prototypes into production systems
- Integrate AI ML solutions with applications
- Integrate pre trained models into production
- Optimize model performance, latency, and cost
Perks/Benefits
- Charity volunteer support
- Equipment provided
- Paid sick days
- Paid vacation
- Professional development days
- Remote work
- Training allowance
- Volunteer day
- Wellness budget
Skills/Tech-stack
AWS | Azure | CI/CD | Cloud platform | Deep learning | Docker | ELT | ETL | Generative AI | Git | Google Cloud | Google Cloud Platform | 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 | PhD
Roles
AI | AI/ML Engineer | Engineer | Learning Engineer | ML Engineer | Machine Learning Engineer
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