Machine Learning Engineer
3 weeks ago
Responsibilities:
- Design, optimize, and deploy machine learning models; implement feature engineering and scaling pipelines.
- Use deep learning frameworks such as TensorFlow and PyTorch; manage models in production using Docker and Kubernetes.
- Automate workflows, ensure model versioning, logging, real-time monitoring, and compliance with security regulations.
- Work with large-scale data, develop feature stores, and implement CI/CD pipelines for model retraining and tracking.
Required Skills:
- Proficiency in machine learning, deep learning, and data engineering (e.g., Spark, Kafka).
- Expertise in MLOps and automation tools (e.g., Docker, Kubernetes, Kubeflow, MLflow, TFX).
- Strong knowledge of model deployment, monitoring, security, compliance, and responsible AI practices.
Nice to Have:
- Experience with A/B testing, Bayesian optimization, and hyperparameter tuning.
- Familiarity with multi-cloud ML deployments and generative AI (e.g., LLM fine-tuning, FAISS).
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