
ML Ops Engineer
4 weeks ago
Position Title: MLOps Engineer
Location: Bangalore(4 days work from office)
Job Type: Full-Time
Experience Level: 3+ Years
Industry:Technology / AI / Data Science
Job Summary:
We are seeking a highly skilled and motivated MLOps Engineer to join our team. The ideal
candidate will be responsible for managing the deployment, monitoring, and optimization
of machine learning models in production environments. You will work closely with data
scientists, software engineers, and DevOps teams to ensure seamless integration and
scalability of AI/ML solutions.
Key Responsibilities:
- Design, develop, and maintain CI/CD pipelines for ML models.
- Collaborate with Data Scientists to build scalable model deployment architectures.
- Automate data and model validation, retraining, and monitoring pipelines.
- Ensure reliability, security, and scalability of ML infrastructure.
- Monitor model performance and data drift in production environments.
- Integrate ML models with APIs, web services, and production systems.
- Implement best practices for version control and reproducibility of ML workflows.
- Manage containerized ML applications using Docker and Kubernetes.
Qualifications:
- Bachelors or Masters degree in Computer Science, Engineering, or a related field.
- Proven experience of 3-7 years in MLOps, DevOps, or ML Engineering roles.
- Proficiency in Python, Bash, and scripting languages.
- Hands-on experience with ML platforms (e.g., MLflow, Kubeflow, SageMaker).
- Familiarity with cloud platforms (AWS, Azure, GCP).
- Experience with CI/CD tools (e.g., Jenkins, GitHub Actions).
- Strong understanding of ML model lifecycle and deployment challenges.
- Excellent problem-solving and communication skills.
Preferred Skills:
- Experience with infrastructure-as-code tools (e.g., Terraform).
- Knowledge of data engineering and ETL pipelines.
- Exposure to monitoring tools like Prometheus, Grafana
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