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Zorba AI
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Hyderabad · On-site · 1-3 Yrs · Sep 28
20 open roles1 posted in 7d20 in 30d
Hiring: Engineering
Job description
Overview
MLOps Engineer / Developer Snapshot Experience: 46 years in ML/AI engineering or DevOps Reports To: MLOps Technical Lead / Manager, AIML
Responsibilities
- Build end-to-end pipelines data ingestion, training, evaluation, packaging, versioning, and deployment. Develop and maintain Jenkins CI/CD for Dev
- QA Production promotion with multi-stage gates. Deploy model-serving APIs on AKS using FastAPI and vLLM; apply ONNX/TensorRT optimizations. Set up observability drift detection (Evidently AI), Prometheus/Grafana, Azure Monitor. Apply DevSecOps practices Key Vault, Managed Identity, SonarQube, Trivy/Snyk. Application Development REST, WebSocket Frameworks using FastAPI
Qualifications
- Reports To: MLOps Technical
- Lead / Manager, AIML
- 4+ years in ML/AI engineering or DevOps with hands-on production MLOps pipeline experience. CI/CD tooling: CI tooling (UV, Ruff, Pyrefly), Jenkins (strong), Azure DevOps, GitOps concepts
- Git and pre-commit workflows. Databricks ML pipelines (Delta Lake, Workflows, MLflow), Asset Bundles and PySpark for data processing. Model serving: FastAPI, Docker, AKS; exposure to vLLM and ONNX/TensorRT optimization. Python (strong FastAPI, Pydantic, async), Bash, YAML/SQL scripting. Cloud knowledge Azure/AWS/GCP Storage, AI related services. Databases and storage: PostgreSQL, Redis, ADLS Gen2. Understanding of containerization, Helm, and infrastructure automation.
Nice to have
- Airflow, DVC, and experiment tracking (W&B / Comet ML). Terraform, KEDA, Azure APIM, and AAD RBAC configuration. LLM fine-tuning pipelines
- Ray Serve or BentoML exposure. Groovy (Jenkinsfile). Manufacturing or semiconductor domain experience.
- Skills: azure,ml,data science,fastapi,pipelines .
Education
- About The Role
- Build and operate the MLOps pipelines that take AI/ML and GenAI models from experimentation to production packaging, CI/CD delivery, model serving, and monitoring. A hands-on engineering role bridging data science and enterprise deployment.
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Job application FAQ
Last updated 27 October 2026
- How do I apply for AI Engineer + ML ops at Zorba AI?
- Open this job on Feedback AI and sign up free (or sign in). You can apply from the job detail page; match scores and skill gaps appear when your profile is complete. Zorba AI may attach structured assessments to interview rounds after you apply.
- Does Feedback AI show a match score for this AI Engineer + ML ops role?
- Yes after you add a resume or skills. Match score ranks this role against your profile — skills met, gaps, level, and location — so you prioritise applications where fit is strongest.
- Is AI Engineer + ML ops remote or on-site in Hyderabad, Telangana?
- This listing is marked on_site with location Hyderabad, Telangana. Confirm details on the job description before applying.
- What skills matter for this AI Engineer + ML ops role at Zorba AI?
- This is a mid-level AI Engineer + ML ops role. Key skills include skills listed in the job description. Feedback AI highlights matched vs missing skills on your profile after signup.