MLOps Engineer
MLOps Engineer
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Salary Not Disclosed
1 Vacancy
Job Description
- Model Development :Collaborate with data scientists to develop train and validate machine learning models.
- RealTime Deployment:
- Utilize cloud services (G CP or AWS) for deploying and scaling machine learning models.
- Architecture:
- Ensure solutions are built for scalability maintainability and high availability.
- Performance Monitoring:
- Implement logging tracking and alerting mechanisms to identify and address model drift or system failures.
Work closely with crossfunctional teams including data engineers software developers and product managers to align on project goals and deliverables. Communicate technical concepts to nontechnical stakeholders effectively.
- Documentation:
- Document best practices and contribute to knowledgesharing initiatives within the team.
Stay uptodate with the latest trends in machine learning and cloud technologies.
- Proactively identify areas for improvement in existing processes and models.
- Qualifications:
Education:
Bachelors degree in Computer Science Data Science Mathematics or a related field. Masters degree preferred.
- Experience:
- Proven experience with realtime model deployment on cloud platforms (AWS GCP).
- Technical Skills:
Strong understanding of data structures algorithms and machine learning concepts.
- Experience with containerization technologies (Docker Kubernetes) for model deployment.
- Knowledge of cloud services like AWS SageMaker Google AI Platform or similar.
- Skills:
Excellent communication skills with the ability to articulate complex ideas to diverse audiences.
- Ability to work in a fastpaced agile environment and manage multiple priorities.
- Preferred Qualifications:
Experience with big data technologies (e.g. Apache Spark Hadoop).
- Familiarity with monitoring and observability tools (e.g. Prometheus Grafana).
Employment Type
Full Time
