MLOps + DevOps Engineer (On-Prem AI Platform)

? Job ID: QTSNB08358

? Experience: 8+ Years

? Work Mode: Work From Office (WFO)

? Location: Pune

? Role Overview

We are looking for a Senior MLOps + DevOps Engineer to architect, build, operate, and scale enterprise AI/ML platforms in an on-premises environment .

The ideal candidate will have robust experience across MLOps, DevOps, ML/LLM deployment, Kubernetes/OpenShift, CI/CD, Linux, GPU infrastructure, monitoring, and production reliability .

This role requires end-to-end ownership of ML systems from data → training → deployment → monitoring .

? Key Responsibilities

Platform Architecture & Ownership

- Design and own end-to-end ML platform architecture.
- Define scalable, secure and reliable MLOps/DevOps standards.
- Standardize MLOps and DevOps frameworks and processes.

Model Deployment & Serving

- Deploy and manage ML/LLM models on GPU-based on-prem infrastructure .
- Optimize inference for latency, throughput and batching.
- Implement model versioning, A/B testing and rollback strategies.

CI/CD & Automation

- Design CI/CD pipelines for ML models, APIs and data workflows.
- Automate testing, deployment and release management.
- Establish repeatable ML deployment processes.

Infrastructure & Containerization

- Manage Linux-based on-prem infrastructure ; RHEL preferred.
- Containerize applications using Docker .
- Deploy and orchestrate workloads using Kubernetes / OpenShift .
- Operate effectively in restricted or air-gapped environments .

Data & System Integration

- Build pipelines integrating structured databases and high-volume logs/streaming data.
- Support both batch and real-time inference architectures.

Monitoring & Reliability





- Implement end-to-end observability across ML models and infrastructure.
- Work with Prometheus, Grafana and ELK Stack .
- Ensure high availability, SLA adherence and effective incident response.

GenAI & Advanced ML

- Deploy RAG pipelines and vector databases .
- Manage LLM serving frameworks.
- Work with agent orchestration frameworks.

Leadership & Collaboration

- Mentor engineers on MLOps and DevOps best practices.
- Collaborate with ML, Data Engineering, Infrastructure and Application teams.
- Lead design reviews and production-readiness assessments.

? Required Skills ✅ 8+ years in MLOps / DevOps / Platform Engineering

✅ Strong Python & Bash scripting

✅ Deep understanding of ML lifecycle and productionization

✅ Production deployment of ML/LLM systems

✅ Linux

✅ Docker

✅ Kubernetes / OpenShift

✅ Jenkins / GitLab CI

✅ SQL & Data Pipelines

✅ Production ML platform scaling experience

⭐ Good to Have

- GPU optimization
- MLflow / Kubeflow
- Terraform / Ansible
- On-premises AI/ML platforms
- Restricted / Air-gapped environments
- RHEL

? Ideal Candidate We are looking for a hands-on MLOps/DevOps platform architect who can operate across both AI/ML systems and infrastructure , driving automation, scalability, security and production reliability.

Strong experience deploying and scaling production ML/GenAI workloads on on-prem GPU infrastructure will be highly valuable.

? Interested candidates can share their updated CV and mention:

Job ID: QTSNB08358 – MLOps + DevOps Engineer

? [email protected]

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📌 MLOps + DevOps Engineer (On-Prem AI Platform) (Hyderabad)
🏢 Qloron
📍 Hyderabad