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Llmops Jobs (NOW HIRING)

ITCAPS LLC

Senior MLOps / LLMOps Engineer

Jersey City, NJ

$109K - $149K/yr

Job Title - Senior MLOps / LLMOps Engineer Kubernetes & AI Inference Platforms Duration - 2 Months Location: New Jersey Job Summary We are seeking a highly skilled Senior MLOps / LLMOps Engineer to ...

AEG

LLMOps Engineer

Brooklyn, NY · On-site

SUMMARY The Large Language Model Ops (LLMOps) Engineer ensures Brooklyn Sports & Entertainment's AI systems are safe to run in production and safe to evolve over time . This role builds and operates ...

Apidel Technologies

AI Sr. Engineer LLMOps & MLOps

Memphis, TN · On-site

$101K - $139K/yr

AI Sr. Engineer LLMOps & MLOps Role Overview This is a high-stakes, execution-focused role within the Transformation Office. We are looking for a "day-one" engineer to own the production lifecycle of ...

SumerSports LLC

LLMOps Platform Engineer

As an ML/AI Engineer on the LLMOps Platform team, you'll build the core infrastructure that powers our AI-first product organization. You'll design, implement, and scale the systems that make it ...

Guru Schools

GCP engineer with GenAI Exp

Phoenix, AZ · On-site

$55/hr

... MLOps / LLMOps for model lifecycle and monitoring Ensure security, governance, and performance optimization Collaborate with business, data, and platform teams to deliver AI-led solutions" Role ...

Lorven Technologies

Cloud Platform Engineer

Charlotte, NC · On-site

$55.75 - $74/hr

GenAI Platforms / LLMs RAG (Retrieval Augmented Generation) MLOps / LLMOps pipelines Key Responsibilities (Keywords for Search): Build enterprise cloud platforms (GCP + Azure) Implement Terraform ...

Gartner

Lead AI Engineer (ML Ops)

Irving, TX · Hybrid

$95K - $125K/yr

High proficiency in MLOps and LLMOps platforms (e.g., MLflow, Kubeflow, Weights & Biases). * Strong DevOps background, including hands-on experience with containerization (Docker, Kubernetes) and CI ...

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Llmops information

What is the difference between Llmops vs Data Scientist?

AspectLlmopsData Scientist
Required credentialsKnowledge of machine learning, AI frameworks, cloud platformsStatistics, programming, data analysis skills
Work environmentAI/ML teams, cloud environments, deployment pipelinesData analysis, modeling, reporting in various industries
Employer usageTech companies, AI startups, research labsFinance, healthcare, tech, retail

While both roles involve working with data and machine learning, Llmops focuses on deploying and maintaining large language models in production environments, requiring expertise in AI infrastructure. Data Scientists primarily analyze data, build models, and generate insights. Llmops professionals ensure models operate efficiently at scale, whereas Data Scientists develop the models and interpret results.

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Llmops jobs near you
Senior MLOps / LLMOps Engineer

Senior MLOps / LLMOps Engineer

ITCAPS LLC

Jersey City, NJ

$109K - $149K/yr

Other

Posted 25 days ago

Job description

Job Title - Senior MLOps / LLMOps Engineer Kubernetes & AI Inference Platforms

Duration - 2 Months

Location: New Jersey

Job Summary

We are seeking a highly skilled Senior MLOps / LLMOps Engineer to design, deploy, and support enterprise-scale AI/LLM platforms in production environments. The ideal candidate will have strong experience with Kubernetes/OpenShift, NVIDIA TensorRT-LLM, Triton Inference Server, and scalable AI infrastructure. This role focuses on building reliable, secure, and high-performance inference platforms for mission-critical AI applications.

Key Responsibilities

  • Deploy, manage, and troubleshoot containerized AI/LLM applications on Kubernetes/OpenShift platforms.
  • Configure, optimize, and support LLM inference workloads using NVIDIA TensorRT-LLM and Triton Inference Server.
  • Design and maintain scalable MLOps/LLMOps and container deployment pipelines.
  • Build CI/CD workflows for AI models, containers, and infrastructure deployments.
  • Package and deploy AI models across UAT, testing, and production environments.
  • Monitor platform performance, GPU utilization, availability, and operational health.
  • Implement logging, alerting, monitoring, and automated operational support processes.
  • Troubleshoot model deployment, scaling, networking, and load balancing issues.
  • Support model optimization techniques including quantization, pruning, and performance tuning.
  • Create operational runbooks, deployment procedures, health checks, and support documentation.
  • Support backup, restore, disaster recovery, failover, and business continuity planning.
  • Ensure platform security, RBAC, compliance, and governance standards are maintained.
  • Collaborate with AI, infrastructure, DevOps, and operations teams to deliver scalable AI solutions.

Required Qualifications

  • 5+ years of experience in Kubernetes/OpenShift administration and containerized environments.
  • Strong hands-on experience with NVIDIA TensorRT-LLM and Triton Inference Server.
  • Experience deploying and supporting LLM/AI inference services in production.
  • Strong knowledge of Docker, microservices, and API-based architectures.
  • Experience building and supporting MLOps/LLMOps pipelines and CI/CD workflows.
  • Expertise in monitoring, logging, and troubleshooting distributed systems.
  • Experience with NVIDIA GPU infrastructure and AI workload optimization.
  • Understanding of incident management, change management, and operational best practices.
  • Strong problem-solving, communication, and collaboration skills.

Preferred Qualifications

  • Experience with OpenShift AI and enterprise AI platforms.
  • Knowledge of model optimization and inference acceleration techniques.
  • Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
  • Familiarity with Infrastructure as Code (Terraform, Ansible, Helm, etc.).
  • Kubernetes/OpenShift or cloud certifications are a plus.

Apply