AI Operations Platform Consultant

Job Description

W-2 Open Positions Need to be Filled Immediately. Consultant must be on our company payroll, Corp-to-Corp (C2C) is not allowed.

Candidates encouraged to apply directly using this portal. We do not accept resumes from other company/ third-party recruiters -->

Job Overview

Job ID: J53022

Posted Date: 01/22/2026

--> Specialized Area: Machine learning

--> Job Title: AI Operations Platform Consultant

Location: Jersey City, NJ

Duration: 24 Months + Extension

Hourly Rate: Depending on Experience (DOE)

Domain Exposure: Pharmaceuticals, Banking & Finance, Retail, Telecom, Real Estate, IT/Software

--> Work Authorization: US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD, L2-EAD, GC-EAD

Client: To Be Discussed Later

Employment Type: W-2, 1099, C2C Bench Recruiter: Jessy Thomas

-->

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Job Description -->

Job Description:

Brings extensive experience operating large-scale GPU-accelerated AI platforms, deploying and managing LLM inference systems on Kubernetes with strong expertise in Triton Inference Server and TensorRT-LLM.

They have repeatedly built and optimized production-grade LLM pipelines with GPU-aware scheduling, load balancing, and real-time performance tuning across multi-node clusters. Their background includes designing containerized microservices, implementing robust deployment workflows, and maintaining operational reliability in mission-critical environments.

They have led end-to-end LLMOps processes involving model versioning, engine builds, automated rollouts, and secure runtime controls.

The candidate has also developed comprehensive observability for inference systems, using telemetry and custom dashboards to track GPU health, latency, throughput, and service availability.

Their work consistently incorporates advanced optimization methods such as mixed precision, quantization, sharding, and batching to improve efficiency. Overall, they bring a strong blend of platform engineering, AI infrastructure, and hands-on operational experience running high-performance LLM systems in production

Basic Info:

AI Operations Platform Consultant

Experience deploying, managing, operating, and troubleshooting containerized services at scale on Kubernetes for mission-critical applications (OpenShift)

Experience with deploying, configuring, and tuning LLMs using TensorRT-LLM and Triton Inference server.

Managing MLOps/LLMOps pipelines, using TensorRT-LLM and Triton Inference server to deploy inference services in production

Setup and operation of AI inference service monitoring for performance and availability.

Experience deploying and troubleshooting LLM models on a containerized platform, monitoring, load balancing, etc.

Operation and support of MLOps/LLMOps pipelines, using TensorRT-LLM and Triton Inference server to deploy inference services in production

Experience deploying and troubleshooting LLM models on a containerized platform, monitoring, load balancing, etc.

Experience with standard processes for operation of a mission critical system – incident management, change management, event management, etc.

Managing scalable infrastructure for deploying and managing LLMs

Deploying models in production environments, including containerization, microservices, and API design

Triton Inference Server, including its architecture, configuration, and deployment.

Model Optimization techniques using Triton with TRTLLM

Model optimization techniques, including pruning, quantization, and knowledge distillation

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