Position: MLOps Engineer

Level: Senior

Experience: 8 10 years

Location: Noida (hybrid)

Budget: Around 20 LPA

About the role

You own the infrastructure that keeps our AI products running and running accurately long after launch. This is a combined DevOps + MLOps role because the two disciplines now overlap heavily in production AI systems, and wed rather have engineers who think across both than two silos that hand work over a wall.

You build the CI/CD pipelines, manage the cloud infrastructure, and operate the model lifecycle: deployment, monitoring, drift detection, retraining, and rollback. Our commercial model includes keeping client AI systems from silently degrading the 10 15% that unmonitored chatbots typically drop within months of launch.

This is a production-first role. If something breaks in a BFSI clients loan workflow at 2am, youre the person who finds out before they do.

Required qualifications

- 8 10 years in DevOps, SRE, or platform engineering, with the last 2+ years operating production ML or LLM systems (not just shipping models from notebooks to a REST endpoint).

- Strong Python (for tooling and pipeline code) and robust Bash. Working knowledge of Go or one statically-typed language is a plus.

- Production experience with at least one managed ML platform AWS SageMaker, Azure ML, or Google Vertex AI including endpoints, pipelines, and model registries.

- Production experience with Kubernetes and Terraform (or equivalent IaC).





- Hands-on experience with at least one CI/CD platform GitHub Actions, GitLab CI, Jenkins, CircleCI, Argo CD.

- Demonstrable experience with observability tooling Prometheus/Grafana, Datadog, CloudWatch, or the equivalent on Azure/GCP.

- Hands-on experience with drift detection and model monitoring Evidently, WhyLabs, Arize, Fiddler, or a custom-built equivalent you can speak to in detail.

- Solid grasp of cloud cost optimisation youve actually cut cloud bills, not just talked about it.

Preferred qualifications

- LLM-specific observability experience LangSmith, LangFuse, Helicone, Arize Phoenix, or equivalent.

- Experience deploying and operating open-source LLMs on private infrastructure Llama 3, Mistral, vLLM, TGI, Ollama, on bare metal or VPC.

- GPU infrastructure experience provisioning, scheduling, cost management (A100/H100/L4 fleets).

- Experience with feature stores Feast, Tecton, SageMaker Feature Store.

- Familiarity with DPDP Act 2023, HIPAA, and sector-specific compliance requirements (RBI cybersecurity guidelines, IRDAI, etc.).

- Prior on-call experience for production systems with paying clients.

- Experience supporting consulting or services-led engagement models.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 MLOps Engineer (Uttar Pradesh)
🏢 Sparix Global
📍 Uttar Pradesh