- Strong experience in System Integration, Application Development, or Data-Warehouse projects across technologies used in the enterprise space
- Objectoriented languages (e.g., Python, PySpark, Java, C#, C++)
- CI/CD experience (e.g. , Jenkins, GitHub Actions)
- Database programming using any flavors of SQL
- Collaborate with crossfunctional teams to integrate machine learning models into existing systems and workflows.
- Ensure compatibility and interoperability between machine learning components and other enterprise technologies.
- Develop and maintain applications and services required for deploying and serving machine learning models in production.
- Utilize objectoriented languages such as Python, PySpark, Java, C#, or C++ to implement scalable and efficient solutions.
- Design and implement deployment pipelines for machine learning models, including continuous integration and continuous deployment (CI/CD) processes.
- Monitor model performance and health in production environments, implementing strategies for automated scaling and fault tolerance.
- Utilize CI/CD tools such as Jenkins, GitHub Actions, or similar, to automate the build, test, and deployment processes for machine learning solutions.
- Implement best practices for version control, code review, and automated testing to ensure the reliability and reproducibility of deployments.
- Leverage your experience in database programming using SQL to manage and query data required for machine learning projects.
- Optimize database schemas, queries, and indexes to support efficient data processing and model training.
- 26 years of experience in System Integration, Application Development, or Data-Warehouse projects across enterprise technologies.
- Proficiency in objectoriented languages such as Python, PySpark, Java, C#, or C++.
- Experience with CI/CD tools such as Jenkins, GitHub Actions, or similar.
- Strong database programming skills using any flavors of SQL.
- Excellent problemsolving and troubleshooting skills, with a keen attention to detail.
- Ability to work effectively in a collaborative, crossfunctional team environment.
- Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, or scikitlearn.
- Familiarity with containerization technologies such as Docker and orchestration tools like Kubernetes.
- Knowledge of cloud platforms such as AWS, Azure, or Google Cloud.
- Understanding of software development best practices, including Agile methodologies and DevOps principles.
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MLOps Engineer - Bangalore, India - Orbus International
Description
Skills Required :
Job Description :
As a Machine Learning Ops Engineer, you will be responsible for deploying, monitoring, and maintaining machine learning models and infrastructure in production environments.
You will collaborate closely with data scientists, software engineers, and DevOps teams to ensure the seamless integration of machine learning solutions into existing systems.
Your expertise in system integration, application development, and database programming will be essential for the success of machine learning projects.
Key Responsibilities :
System Integration:
Application Development :
Machine Learning Ops :
CI/CD Experience :
Database Programming :
Required Skills and Qualifications :
Preferred Qualifications :
