
Ml Ops Engineer
6 days ago
ML Ops Engineer
**Location**: Hong Kong, Singapore
**Key Responsibilities**:
- Develop and manage MLOps infrastructure to facilitate the deployment, scaling, and monitoring of machine learning models.
- Work collaboratively with data scientists and engineering teams to move machine learning models from development to production smoothly.
- Implement and manage automation tools for continuous integration, testing, and deployment of machine learning systems.
- Monitor the performance of machine learning models in production, making optimizations as necessary.
- Keep up-to-date with the latest trends and advancements in MLOps, machine learning frameworks, and DevOps methodologies.
**Qualifications**:
- Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or a related field.
- Proven experience in MLOps, with a strong background in machine learning and DevOps practices.
- Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch) and DevOps tools (e.g., Docker, Kubernetes, Jenkins).
- Knowledge of CI/CD pipelines, automation processes, and cloud infrastructure.
- Proficiency in troubleshooting and optimizing machine learning models and related infrastructure.
- Excellent English communication skills, both written and verbal.
- Effective problem-solving skills and a collaborative team-working ethos.
**Job Types**: Full-time, Contract
Contract length: 6-12 months
**Salary**: From $5,000.00 per month
Supplemental pay types:
- Overtime pay
- Performance bonus
**Experience**:
- MLOps: 1 year (required)
- TensorFlow, PyTorch: 1 year (required)
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