MLOPS Azure Engineer

2 months ago

Anywhere in IndiaMultiple Locations Randstad Full time

Job Description :

- Lead MLOps initiatives, collaborating with key stakeholders to strategize, plan, and deliver projects.

- Design, develop, and deploy complex AI/ML solutions on cloud infrastructure, ensuring scalability for changing business and technical needs.

- Create infrastructure and architecture diagrams for projects.

- Project manage, allocate tasks to junior ML engineers, and ensure project closure.

- Enhance coding practices, conduct code reviews, and implement best practices for model management.

- Provide thought leadership on new technologies, tools, and suggest improvements.

- Support the interview process for hiring both junior and senior ML engineers.

- Specialize in the deployment, monitoring, and maintenance of AI models in production.

- Collaborate with governance lead and data scientists to institutionalize best practices.

- Build deployment pipelines, implement automation, and specialize in containerization and orchestration (e.g., Docker, Kubernetes).

- Implement continuous integration and continuous deployment (CI/CD) for efficient workflows.

- Focus on scalability and resource management.

Primary Skills/Technical Stack :

- MLOps

- Cloud Infrastructure

- ML Engineering &ML Ops workflows & tools

- Deployment, Monitoring, and Maintenance of AI Models

- Deployment Pipelines,Automation

- Containerization (e.g., Docker)

- Orchestration (e.g., Kubernetes)

- Continuous Integration and Continuous Deployment (CI/CD)

Secondary Skills/Good to Have :

- Expertise in specific cloud platforms (e.g., AWS Sagemaker, Azure, Google Cloud)

- Experience with specific programming languages (e.g., Python, R)

- Understanding of data governance and compliance

- Background in software development practices

- Experience with version control systems (e.g., Git)

- Proficiency in scripting languages for automation

- Understanding of DevOps principles and practices

(ref:hirist.tech)

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