AI Platform Engineer

Job not on LinkedIn

🕒 January 30

🇮🇳 India – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🏗️ Platform Engineer

👻 Ghost score 57%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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AHEAD

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

💼 Consulting

🤖 Artificial Intelligence

🏢 Enterprise

💰 $5.7M Venture Round - AHEAD on 2024-05

Consulting • Artificial Intelligence • Enterprise

AHEAD is a technology consulting and systems-integration firm that accelerates digital transformation by engineering integrated solutions across infrastructure, applications, data, and security. The company specializes in AI transformation and AI-enabled infrastructure, data platform and platform/workload modernization, secure and resilient architectures, operational excellence, and managed services including IT lifecycle and procurement (AHEAD Hatch) and hardware integration (AHEAD Foundry). AHEAD delivers end-to-end services from strategy and financial consulting to build and run operations, partners with major cloud and infrastructure vendors (AWS, Google Cloud, Microsoft, Cisco, Dell, VMware, NVIDIA, ServiceNow, Palo Alto Networks, Rubrik, etc. ), and serves enterprise clients across industries such as healthcare, financial services, manufacturing, retail, and public sector.

📋 Description

• Architect and manage Kubernetes clusters tailored to AI/ML workloads. • Implement Run:ai and operators for GPU resource orchestration and workload scheduling. • Develop and maintain Python-based automation scripts and ML pipelines; automate infrastructure provisioning with Terraform and configuration management with Ansible. • Create and manage Jupyter Notebooks for experimentation and collaboration. • Integrate and optimize NVIDIA Enterprise Suite components (CUDA, NeMo Framework, Triton, TensorRT, GPU drivers) for accelerated computing. • Establish and maintain MLOps best practices for model lifecycle management, CI/CD, and monitoring (e.g., MLflow, Kubeflow). • Work closely with data scientists and platform engineers to ensure efficient resource utilization and scalability across environments.

🎯 Requirements

• 4+ years in platform architecture or solutions architecture, with 2+ years focused on AI/ML workloads. • Experience with high-performance computing (HPC) environments. • Familiarity with distributed training and model optimization techniques. • Certification in Kubernetes or cloud platforms (AWS, Azure, GCP). • Strong proficiency in Python and experience with ML frameworks (TensorFlow, PyTorch). • Hands-on experience with Kubernetes and container orchestration. • Familiarity with Run:ai or similar GPU scheduling platforms. • Expertise in Terraform and Ansible for infrastructure automation. • Experience with Jupyter Notebooks for ML development. • Knowledge of NVIDIA Enterprise Suite (CUDA, NeMo Framework, Triton, GPU drivers). • Solid understanding of MLOps principles and tools (e.g., MLflow, Kubeflow). • Background in deploying and scaling AI workloads in cloud or hybrid environments.

🏖️ Benefits

• India Employment Benefits include: