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dataeconomy

MLOps / Serving Engineer

Hyderabad · Senior

Older listing - lower visibility likelyVerified listingPosted 40d ago

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Skills required

14 listed
Triton Inference ServerTerm Life InsuranceMLOps (Machine Learning Operations)Large Language Models (LLMs)Amazon Web ServicesTensorRTGraphics Processing Unit (GPU)Throughput+6 more
Triton Inference ServerTerm Life InsuranceMLOps (Machine Learning Operations)Large Language Models (LLMs)Amazon Web Services

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Job description

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 & flexible 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.

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Applicants who checked fit first are 3.1× more likely to hear back

Your match scoreFree · sign in
86Overall
64Skills
97Experience

Your score for this role already exists

ASAI compared this JD against 41 signals - skills, seniority, domain, stack overlap etc. Add a resume and it unlocks in about 30 seconds.

Always free · no credit card · 1 tap with Google

Free · no signup

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Join WhatsAppJoin Telegram

No spam. Just jobs and resources.

Why people use ASAI

Someone shared one job with you. ASAI keeps finding the rest.

  • Scored, not searched. Every role ranked against your actual profile.

  • Alerts as often as hourly. Reach new roles while the pile is still small.

  • Skill gaps, spelled out. See exactly which requirements you don't meet yet.

  • Verified jobs, only. Say no to ghost jobs. Your time deserves respect.

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