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 Advantages:

PF and Gratuity provided as per standard g

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