
Senior Machine Learning Engineer
21 hours ago
Job Overview
We are seeking an experienced Data Scientist to design, build, and deploy robust machine learning models in a production environment using AWS SageMaker.
Key Responsibilities:
- Design and develop end-to-end machine learning pipelines on AWS SageMaker.
- Collaborate with data scientists to translate models and algorithms into production-ready code.
- Manage the entire machine learning lifecycle, including data ingestion, model training, validation, and deployment.
- Implement MLOps best practices to automate workflows and ensure model performance and reliability.
- Optimize ML models for performance, scalability, and cost efficiency on the AWS platform.
- Monitor and troubleshoot deployed models to ensure they meet performance and business requirements.
- Stay current with the latest advancements in machine learning and cloud technologies.
Required Skills and Qualifications:
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- 3+ years of experience in a machine learning or data science role.
- Hands-on experience with AWS services, specifically SageMaker.
- Proficiency in Python and standard ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).
- Experience with containerization technologies like Docker.
- Solid understanding of MLOps principles and tools for CI/CD.
- Knowledge of data engineering principles and experience with big data technologies (e.g., Spark, Hadoop).
- Strong problem-solving skills and the ability to work in a collaborative environment.
Benefits:
- Opportunity to work with cutting-edge technology.
- Collaborative and dynamic work environment.
- Professional growth and development opportunities.
Others:
- Work closely with cross-functional teams to drive innovation.
- Contribute to the development of new features and functionalities.
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