Senior ML Engineer
Tasks
- Architect production ready ML systems
- Build and deploy AI solutions at scale
- Build and maintain data pipelines
- Deploy models using cloud native and serverless architectures
- Design machine learning models
- Develop and optimize NLP and generative AI solutions
- Develop end-to-end ML pipelines
- Ensure security privacy and compliance in ML workflows
- Implement MLOps workflows
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Cloud Computing | Cloud platform | Data Pipelines | Docker | Feature Engineering | Generative AI | Google Cloud | Google Cloud Platform | Hugging Face | Hugging Face Transformers | Kubernetes | Language Models | Language Processing | Large Language Models | MLOps | Machine Learning | Microsoft Azure | Model Evaluation | Natural Language | Natural Language Processing | PyTorch | Python | Serverless computing | TensorFlow
Education
N/A
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