
Lead - Software Engineer MLOps
cloudsufi
Posted 2026-06-23
INR 3,500,000 - INR 4,000,000 per year
Tech & Engg
Job Description
Ovii's Interpretation of the Role
Lead MLOps Engineer (30% leadership, 70% hands‑on) responsible for designing, scaling and operating machine‑learning pipelines on Google Cloud Platform while guiding a small engineering team.
Role Snapshot
- Lead MLOps Engineer (30% leadership, 70% hands‑on)
- Design & scale ML pipelines on GCP
- Automate model deployment, monitoring & governance
- Guide a small engineering team
- Collaborate with data scientists and data engineers
Must-Have Requirements
- MLOps
- Google Cloud Platform services (Vertex AI, GKE, BigQuery, Cloud Build, Cloud Storage, Cloud Endpoints)
- CI/CD pipelines for ML model deployment
- Data catalog tools (e.g., Open Metadata)
- Model serving frameworks (TensorFlow Serving, TorchServe)
- Kubeflow, MLflow, TFX
- Google Cloud Platform
- Project lead
- University degree in Mathematics, Statistics, Computer Science, Physics or similar
Nice-to-Have Signals
- Google Cloud official certifications
- Google Cloud certifications
Work Setup
- Location: -, India
- Employment type: Full-Time
What You'll Likely Work On
- Architect, build and maintain scalable MLOps pipelines using GCP services such as Vertex AI, GKE, Cloud Storage and BigQuery
- Implement and optimize CI/CD pipelines for machine‑learning model deployment
- Manage data catalog tools for versioning, lineage tracking and governance of models and datasets
- Develop automated monitoring, logging and performance‑tracking systems for models in production
- Lead integration of data‑cataloging solutions (e.g., Open Metadata) across the organization
- Collaborate closely with data scientists and data engineers to streamline data processing, model training and testing
- Mentor the engineering team and coordinate with cross‑functional stakeholders
- Stay current with emerging MLOps trends and best practices
Good Fit If You Have
- Strong analytical and problem‑solving abilities for complex MLOps challenges
- Excellent English communication and presentation skills
- Proven experience leading projects in an international setting
Skills
- MLOps
- Google Cloud Platform (Vertex AI, GKE, BigQuery, Cloud Build, Cloud Storage, Cloud Endpoints)
- CI/CD pipelines for ML
- Data cataloging tools (e.g., Open Metadata)
- Model serving frameworks (TensorFlow Serving, TorchServe)
- Kubeflow / MLflow / TFX
- English proficiency
- Analytical & problem‑solving