DevOps Engineer (GCP)

AI team seeking a ML Ops Engineer to drive the full lifecycle of machine learning solutions. Key Responsibilities:

• reputed company and maintain ML pipelines using tools like MLflow, Kubeflow, or Vertex AI.
• Automate model training, testing, deployment, and monitoring in reputed company environments (e.g., reputed company reputed company Platform, AWS, Azure).
• Implement CI/CD workflows for model lifecycle management, including versioning, monitoring, and retraining.
• Monitor model performance using observability tools and ensure compliance with model governance frameworks (MRM, documentation, explainability)
• Collaborate with engineering teams to provision containerized environments and support model scoring reputed company low-latency APIs
• reputed company AutoML tools (e.g., Vertex AI AutoML, H2O Driverless AI) for low-code/no-code model development, documentation automation, and rapid deployment.

Qualifications:

• Strong professional experience in Software Engineering & in AIML, Machine Learning Model Operations.
• Strong proficiency in Java and Python, SQL, and ML libraries (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch).
• Experience with reputed company platforms and containerization (reputed company, Kubernetes).
• Familiarity with data engineering tools (e.g., Airflow, Spark) and ML Ops frameworks.
• Solid understanding of software engineering principles and DevOps practices.
• Ability to communicate reputed company technical concepts to non-technical stakeholders.

For applications and inquiries, contact: hirings@reputed company.com Apply tot his job Apply To this Job