Job Title: MLOps

/ Serving Engineer

Experience : 5+ years

Location : Hyderabad OR Pune

Notice Period: 0-30 days

Work mode - Hybrid

We are seeking an experienced MLOps

/ Serving Engineer who can design and operate the production serving infrastructure for fine-tuned LLMs on AWS — optimised inference engines, shadow-mode and staged rollout pipelines, monitoring dashboards, and the path from experimental model to full production traffic.

Key Responsibilities:

- Deploy fine-tuned LLMs using vLLM, TensorRT-LLM, or Triton with continuous batching on AWS GPU instances
- Build shadow-mode deployment: run fine-tuned model alongside production, log comparison data without impacting live traffic
- Execute staged rollout: canary (5%) → gradual ramp (25% → 50% → 100%) with automated rollback on quality degradation
- Optimize inference for input-heavy workloads (~17K token inputs, ~130 token outputs): prefill throughput, KV-cache, INT8 quantization
- Build monitoring dashboards: latency, throughput, accuracy metrics, cost per request
- Design auto-scaling; implement high-availability (2× instances); automated rollback triggers on end-to-end quality metrics

Requirements

- 5+ years MLOps or ML infrastructure engineering




- Hands-on with vLLM, TensorRT-LLM, or Triton Inference Server
- Deep familiarity with g5, p4de, p5 instance families, EC2 auto-scaling
- Have worked on Deployment patterns like Shadow-mode, canary, A/B traffic routing, automated rollback
- Experience onto Continuous batching, INT8 quantization, KV-cache management
- Expertise on Docker, Kubernetes (EKS) for ML workloads
- Worked on CloudWatch, Prometheus, Grafana

Benefits

- Comprehensive Medical Coverage: Health insurance of INR 5.0 Lakhs for you and your family (up to 6 members), ensuring complete peace of mind.

- Robust Protection Plans: Group Personal Accident Insurance and Group Term Life Insurance to safeguard you and your loved ones.

- Retirement Benefits: PF and Gratuity provided as per standard government regulations.

- Flexible Work Options: Enjoy hybrid work arrangements & versatile working hours

- Generous Leave Policy: 21 days of annual leave, in addition to 10 company-declared holidays.

- Employee Well-being Spaces: Access to a dedicated break-out area with round-the-clock refreshments for relaxation and rejuvenation.

📌 MLOps / Serving Engineer (Hyderabad)
🏢 DataEconomy
📍 Hyderabad