Senior Machine Learning Engineer
Tasks
- Build data pipelines
- Build machine learning workflows
- Deploy machine learning models
- Design machine learning models
- Ensure code quality and documentation
- Evaluate AI and ML technologies
- Implement MLOps for deployment monitoring and retraining
- Integrate AI solutions into products
- Maintain software engineering best practices
- Mentor junior engineers
- Monitor model performance and reliability
- Optimize model performance
- Process structured data
- Process unstructured data
- Research emerging AI and ML technologies
- Test machine learning models
- Train machine learning models
Perks/Benefits
- Career growth opportunities
- Collaborative work environment
- Exposure to cutting edge AI and machine learning technologies
- Innovation driven work environment
Skills/Tech-stack
AWS | Airflow | Apache Spark | Azure | Cloud platform | Computer Vision | Docker | Fine Tuning | Generative AI | Google Cloud | Google Cloud Platform | Kubeflow | Kubernetes | Language Models | Language Processing | Large Language Models | MLflow | Microservices | MongoDB | MySQL | Natural Language | Natural Language Processing | NoSQL | NumPy | Pandas | PostgreSQL | PyTorch | Python | REST APIs | Redis | Reinforcement Learning | Retrieval-Augmented Generation | SQL | Scikit-learn | TensorFlow | Vector Databases | XGBoost
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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