Cloud Native MLOps Engineer
4 days ago
We are looking for a highly motivated Cloud Native MLOps Engineer to join our team and contribute to the development of innovative machine learning solutions. As a key member of our team, you will be responsible for designing, building, and maintaining scalable machine learning platforms.
Key Responsibilities:
- Design and develop cloud-native machine learning infrastructure using AWS, GCP, or Azure.
- Implement ML pipelines, model training, validation, and deployment workflows.
- Collaborate with data science teams to provide infrastructure and tools for seamless collaboration.
- Optimize model inference and training performance on various hardware architectures.
- Ensure security and compliance with relevant regulations and standards.
Requirements:
- 3+ years of experience in software engineering or infrastructure roles, with a focus on machine learning platforms or MLOps.
- Strong experience with cloud platforms, containerization technologies (Docker), and orchestration tools (Kubernetes).
- Proficiency in programming languages such as Python, and familiarity with ML libraries and frameworks.
- Familiarity with CI/CD pipelines tailored for machine learning.
- Bachelor's degree in Computer Science, Data Engineering, Machine Learning, or a related field.
Estimated Salary: $150,000 - $180,000 per year.
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