Qureos

FIND_THE_RIGHTJOB.

MLOps Engineer (Triton + GPU + Production AI)

JOB_REQUIREMENTS

Hires in

Not specified

Employment Type

Not specified

Company Location

Not specified

Salary

Not specified

Job Description – MLOps Engineer (Triton + GPU + Production AI)

Immediate joining.
Employment Type: Full-time
Project: OTRAS – Next-Gen AI-based Government Exam & Recruitment Platform

MLOps Engineer (Triton + GPU + Production AI)

Role: MLOps Engineer

Experience: 5–10 Years

Location: Andhra Pradesh

Salary: ₹1,00,000 – ₹1,50,000 per month

About the Role

We are building OTRAS, India’s largest next-gen AI-based examination platform serving 250M+ candidates per year.

We need an experienced MLOps Engineer who can productionize large AI/ML models (OMR, OCR, face recognition, fraud detection) using NVIDIA Triton, ONNX, TensorRT, and GPU pipelines.

You will be responsible for deploying, scaling, monitoring, and optimizing AI workloads in a distributed Kubernetes environment.

Key Responsibilities

Model Deployment & Serving

  • Deploy PyTorch/TensorFlow models on NVIDIA Triton Inference Server
  • Convert models to ONNX and optimize using TensorRT
  • Implement batching, dynamic batching, and GPU scheduling
  • Build scalable inference APIs (HTTP/gRPC)

Infrastructure & Automation

  • Deploy and manage AI workloads on Kubernetes (GPU node pools)
  • Automate model CI/CD using GitHub Actions + ArgoCD
  • Setup model versioning, canary deployments, and rollback workflows
  • Manage the Triton model repository & configs

Monitoring & Optimization

  • Implement inference metrics (latency, TPS, GPU utilization)
  • Setup monitoring using Prometheus + Grafana
  • Optimize inference speed and memory with TensorRT
  • Run load tests for 10M+ inference events

Data & Pipelines

  • Build ETL workflows for AI datasets
  • Automate dataset cleaning, preprocessing
  • Integrate with ClickHouse / S3 storage
  • Create pipelines for:
  • ✔ OMR data ingestion✔ ID card OCR✔ Face detection & liveness scoringSecurity & Reliability
  • Ensure secure model access (token-based + mTLS)
  • Handle production failures, logs, distributed tracing
  • Implement AI/ML model audit trails

Required Skills

  • 4+ years experience in MLOps or ML Engineering
  • Strong hands-on with:
  • ✔ NVIDIA Triton Inference Server✔ ONNX / ONNX Runtime✔ TensorRT✔ PyTorch or TensorFlow✔ CUDA (basic understanding)
  • Strong in Docker & Kubernetes
  • Experience with CI/CD
  • Knowledge of GPU scaling, batching, and memory optimization
  • Experience working with large-scale ML systemsBonus Skills
  • Experience with Airflow or Kubeflow
  • Experience with model quantization
  • Familiarity with computer vision
  • Knowledge of message queues (Kafka)
  • Worked on AI for ID verification / OMR / OCR

Why Join OTRAS?

  • Build India’s first AI-powered exam infrastructure
  • Work with Go microservices + Kubernetes + Triton
  • Massive impact (250M candidates)
  • Fast-moving, high-performance engineering culture
  • High visibility role with strong growth

Job Types: Full-time, Permanent, Volunteer

Pay: ₹180,000.00 - ₹1,080,070.03 per year

Benefits:

  • Health insurance
  • Life insurance
  • Provident Fund

Ability to commute/relocate:

  • Guntur, Andhra Pradesh: Reliably commute or planning to relocate before starting work (Required)

Work Location: In person

© 2025 Qureos. All rights reserved.