Real job — pulled straight from Tarento’s careers page · Verified September 30, 2026 · No reposts.
Job description
Tarento is hiring a AI ML Ops Engineer — a full-time, based in Indore, India role. Apply directly on Tarento's careers page below.
AI ML Ops Engineer
Location: Indore, India
Department: Digital
Experience: 3-5 Years
Skills: Linus, GCP, CICD, kubernetes, azure, monitoring tools, python, Docker, AWS
- CI/CD for ML: Build and maintain automated pipelines for model training, testing, and deployment.
- Infrastructure: Containerize and orchestrate model-serving infrastructure (Docker, Kubernetes) at scale.
- Monitoring: Set up monitoring for model performance, data/concept drift, latency, and system health.
- Versioning & Reproducibility: Manage model/experiment versioning and reproducibility (MLflow, DVC, or similar).
- Cloud & GPU Management: Manage scalable, cost-efficient GPU/cloud infrastructure for training and inference workloads.
- Strong hands-on experience with Docker and Kubernetes
- CI/CD tooling (GitHub Actions, Jenkins, GitLab CI, or similar)
- Experience with model-serving frameworks (Triton Inference Server, TorchServe, or similar)
- Cloud platform experience (AWS/Azure/GCP), especially GPU infrastructure
- Python for automation and tooling
- Experience with experiment tracking and model registries (MLflow, DVC, Weights & Biases)
- Monitoring/observability tooling (Prometheus, Grafana, or similar)
- Production experience with Triton Inference Server: model repositories, ensembles, dynamic batching, instance groups
- GPU operations on Kubernetes: NVIDIA GPU Operator, MIG/time-slicing, node pools, driver/CUDA version management
- Hands-on with TensorRT / ONNX Runtime conversion and performance profiling (Nsight, perf_analyzer) gRPC and streaming service patterns; load testing tools (Locust, k6)
- Strong Linux, networking and debugging fundamentals for bare-metal environments
- Docker, Kubernetes, CI/CD, Python, cloud infrastructure (AWS/Azure/GCP)
- Experience deploying LLM/NLP inference services specifically (batching, quantization, low-latency serving)
- Familiarity with vLLM, Ollama, or similar for local LLM hosting
- Infrastructure-as-code experience (Terraform, Helm)
- Experience with NVIDIA NVCF, NeMo or NIM deployments
- Serving TTS/ASR models where time-to-first-byte matters
- Log/trace stacks (Loki, OpenTelemetry, ELK) and on-call tooling
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Frequently asked questions
What skills are required for AI ML Ops Engineer at Tarento?
The required skills for AI ML Ops Engineer at Tarento include: Docker, Kubernetes, CI/CD, Python, AWS, Azure, GCP, Linux, MLflow, Prometheus, Grafana, gRPC, Terraform, Helm, OpenTelemetry, Elasticsearch.
What is the seniority level for AI ML Ops Engineer at Tarento?
AI ML Ops Engineer at Tarento is a Mid Level / Senior level position.
How do I apply for AI ML Ops Engineer at Tarento?
You can view the full description and apply for AI ML Ops Engineer at Tarento on EchoJobs: https://echojobs.io/job/tarento-ai-ml-ops-engineer-2dc9f.