ML Ops Engineer Turing Global India
Turing Global India
Office Location
Full Time
Experience: 3 - 5 years required
Pay: INR 1 - INR 10001 /Month
Type: Full Time
Location: Remote
Skills: Cloud Computing, continuous integration, Automation, orchestration, Cloud Security, GCP, Machine Learning, Cloud
About Turing Global India
Job Description
Job Responsibilities:
- Architect and establish cloud infrastructure and data workflows to facilitate the deployment of large-scale machine learning models in production environments.
- Define and promote best practices for MLOps to ensure high standards of quality, consistency, and automation across the organization.
- Innovate and implement continuous integration and delivery (CI/CD) pipelines, enabling swift iteration and deployment of ML models and systems.
- Collaborate with cross-functional teams to identify, create, and integrate tools and services optimally supporting ML processes, from training and tuning to inference.
- Keep abreast of emerging technologies and propose integration strategies to enhance ML system performance, maintainability, and reliability.
- Contribute to ML systems security, traceability, versioning, and automate the deployment of proof-of-concept projects to production.
Job Requirements:
- Minimum of 3 years of experience in building and deploying end-to-end machine learning projects in a similar role as an ML Ops Engineer, ML Platform Engineer, or ML Engineer.
- Proficient knowledge of popular machine learning frameworks, including PyTorch, Tensorflow, and associated technologies.
- Profound software engineering skills, with a strong command of Python and cloud computing environments.
- Solid understanding of cloud security principles and compliance standards within platforms such as AWS and GCP.
- Expertise in scalable database systems and proficient experience in developing CI/CD pipelines in cloud-based architectures.
- Proven experience in containerization technologies and orchestration tools like Kubernetes and Terraform.
- Demonstrated ability to develop custom API integrations and familiarity with data orchestration frameworks.
- Autonomous and innovative problem-solving skills, with the ability to lead, impactful initiatives in a dynamic and uncertain landscape.