
Senior Machine Learning Engineer
2 weeks ago
About the Role:
We're seeking a seasoned Data Modeler to craft, deploy, and refine machine learning models that power our business-critical solutions.
Key Responsibilities:
- Model Development: Design, develop, and deploy regression, classification, clustering, and deep learning models.
- Data Pipeline Management: Build and optimize data pipelines, feature engineering, and training workflows.
- Deployment: Deploy models to production using Docker, Kubernetes, and cloud platforms like AWS/GCP/Azure.
- Performance Monitoring: Monitor model performance, retrain, and maintain production-ready systems.
- API Development: Develop APIs and integrate ML solutions with enterprise applications.
- Knowledge Sharing: Stay updated on ML/AI trends and contribute innovative solutions.
- Collaboration: Collaborate with data scientists, engineers, and product managers to align with business goals.
Requirements:
- 3+ years of experience in ML engineering or related field.
- 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.
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