
Machine Learning Engineer
3 weeks ago
About the Role :
- Build and optimize data pipelines, feature engineering, and training workflows.
- Deploy models to production using Docker, Kubernetes, and cloud platforms (AWS/GCP/Azure).
- Monitor model performance, retrain, and maintain production-ready systems.
- Develop APIs and integrate ML solutions with enterprise applications.
- Stay updated on ML/AI trends and contribute innovative solutions.
- Collaborate with data scientists, engineers, and product managers to align with business :
- Strong proficiency in Python; knowledge of Java/Scala/R is a plus.
- Expertise with ML libraries/frameworks : scikit-learn, TensorFlow, PyTorch, Keras.
- Hands-on with data tools : Pandas, NumPy, Spark.
- Experience with ML deployment (SageMaker, Azure ML, GCP AI, TensorFlow Serving, TorchServe).
- Familiarity with databases (SQL, MongoDB, Cassandra) and version control (Git).
- Understanding of DevOps/MLOps practices.
- Excellent problem-solving, communication, and collaboration skills.
(ref:hirist.tech)-
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