MLOps Engineer-2

About the Company
Embitel Technologies is a Volkswagen AG (VW) Group Company. VW is a German multinational automotive manufacturing corporation headquartered in Wolfsburg, Germany. VW is one of the world’s largest automaker by sales. VW sold 10.9 million vehicles in 2019. The group comprises of 12 brands from seven European Countries: Volkswagen, Audi, Lamborghini, Porsche, Bugatti, Bentley, Ducati (motorcycles), Skoda, SEAT, Scania, MAN and Volkswagen commercial vehicles.

About CARIAD (Car, I Am Digital)

The automotive industry is in disruption. As a company, CARIAD is playing a part in multiple large trends at the same time: electrification, automation, and digitalization. The new name builds on changing customer needs. Automotive customers are demanding more comfort, more safety, more sustainability, and more connectivity. With its software platforms and digital features, CARIAD is developing solutions and products that will turn the car into a smart companion to accompany customers into the future with continuous updates and new digital features, even years later. The new company name reflects this zeitgeist: ‘Car, I Am Digital’. The brand profile can be found on its new website .

Currently, around 4,000 employees are working at CARIAD on the digital transformation of the car. CARIAD is working intensively on the software and technology platform for Premium Platform Electric (PPE). The first vehicles based on PPE will be the electric Porsche Macan and Audi Q6 e-tron. At the core of CARIAD is the development of the unified and scalable software and technology platform E³ 2.0 for all Group brands. E³ stands for ‘end to end electronics architecture’. The new software and technology platform is built from scratch and will be used first at the end of 2024 in Artemis, the lighthouse project of Audi. As of 2026, E³ 2.0 is due to be scaled by the Volkswagen brand with Trinity in the volume segment.

About our Group

CARIAD COE (Centre of Excellence) is setup in Bangalore, India working exclusively with CARIAD and associated VW groups with the focus on development of ‘VW.OS”. The areas of work involve development of platform components such as firmware, boot loaders, AUTOSAR, Linux/QNX BSP, Service oriented architecture-based middleware components.

Job Description:

About the Role:

We are looking for an MLOps Engineer to own, develop, and maintain our ML deployment infrastructure — spanning an Argo-based GitOps workflow orchestration platform and a Python framework for large-scale AI model inference.

Relevant Experience : 4 to 6 years

Job Description:

Infrastructure & Pipeline Development:

- Design and maintain Argo Workflows / Argo Events–based ML pipelines with customize overlays across environments (dev / QA / staging / prod).

- Author WorkflowTemplates (DAGs, fan-out patterns, cron triggers, webhook integrations) following GitOps best practices.

- Build Docker images for GPU-accelerated inference (NVIDIA CUDA, multi-stage builds).

- Implement Ray-based distributed compute pipelines for scalable model inference.

- Integrate with Azure ML for model versioning, registry, and continuous training.

- Maintain CI/CD pipelines with quality gates, automated testing, and container image promotion.

Model Deployment & Operations:

- Automate deployment, monitoring, and rollback of deep learning models (object detection, semantic segmentation, classification, etc.) on production Kubernetes clusters.

- Manage model versioning and artifact management from cloud ML workspaces to production containers.

- Maintain configuration systems for reproducible pipeline execution.

- Monitor model performance, data drift, and pipeline health; build observability dashboards.

- Troubleshoot production issues — failing workflows, GPU resource contention, data bottlenecks, and latency regressions.

Expertise and Qualifications:

Must-Have Technical Skills

- Python — packaging (setuptools_scm, uv).

- Kubernetes — workload orchestration, GPU scheduling, namespace management.

- Argo Workflows / Argo Events — WorkflowTemplates, DAGs, event-driven triggers.

- Docker — multi-stage builds, CUDA-based images, container optimization.

- GitOps — Customize overlays, environment promotion.

- Azure Cloud — Azure ML, Azure Blob Storage, AKS.

- CI/CD — pipeline design; quality gates (SonarQube or equivalent).

- Linux — command-line proficiency; shell scripting.

Good-to-Have Technical Skills

- Ray — distributed data processing and inference at scale.

- Deep Learning frameworks — PyTorch, TensorFlow; model formats (ONNX, SavedModel, TorchScript).

- Databricks / Spark SQL, Helm / ArgoCD, Prometheus / Grafana.

Soft Skills

- Strong communication — explain complex infrastructure to data scientists and new engineers simply.

- Ownership mindset — proactively identify and fix reliability gaps.

- Collaboration — work across data science, perception, DevOps, and QA teams.

- Problem-solving under pressure — triage and resolve production issues quickly.

Working with Embitel
• Freedom to challenge norms, make mistakes, learn and grow
• There is no ‘I’ in word ‘Team’ and no hierarchy at Embitel
• Employees of Embitel are partners of our excellence and growth. And they are at the core of
organization’s Mission and Vision

To explore an exciting & progressive Career development at Embitel India:
• Visit us at: www.embitel.com
• Follow us at LinkedIn: