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Cortex is hiring for MLOps Engineer WORK FROM OFFICE Notice; Immediate to 30days Roles And Responsibilites - Design and implement end-to-end CI/CD pipelines for machine learning - Build and maintain automated pipelines for model training, validation, deployment, and rollback, enabling reliable and repeatable ML releases into production. - Own and operate the ML platform using Google Vertex AI - Set up, configure, and manage Vertex AI for model training, experimentation, deployment, and inference, ensuring scalability, security, and cost efficiency. - Enable automated model re-training and lifecycle management- Develop data- and performance-triggered re-training workflows to ensure models remain accurate and relevant as data patterns evolve. - Implement robust model monitoring and observability - Establish monitoring for model performance, data drift, prediction quality, and pipeline health, with alerting and dashboards for proactive issue detection. - Ensure production-grade reliability, governance, and collaboration - Enforce versioning, lineage, reproducibility, and auditability across ML workflows, while collaborating closely with data scientists, engineers, and product teams. - Programming & ML Engineering - Strong proficiency in Python for ML pipelines, automation, and backend services and Working knowledge of ML frameworks such as TensorFlow, PyTorch, or Scikit-learn - MLOps & CI/CD - Familiarity with pipeline orchestration (Kubeflow Pipelines, Vertex AI Pipelines, Airflow) and Understanding of ML lifecycle management (training, validation, deployment, rollback) - Cloud & Platform (GCP Preferred) - Robust experience with Google Cloud Platform, especially Vertex AI - Containers, Infrastructure & DevOps - Hands-on experience with Docker and containerized ML workloads and Familiarity with Kubernetes (GKE preferred) - Monitoring, Observability & Data Quality - Understanding of data validation and quality checks in ML pipelines and Experience with model monitoring (performance, drift, bias) If interested please forward your resumes This job is posted by Aishwarya.K Business HR Cortex Consultants .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.