AI Platform Engineer
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Requirements
• 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. • 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).
Responsibilities
• Kubernetes for AI/ML: Architect and manage Kubernetes clusters tailored to AI/ML workloads. • GPU Orchestration: Implement Run:ai and operators for GPU resource orchestration and workload scheduling. • Automation & Pipelines: Develop and maintain Python-based automation scripts and ML pipelines; automate infrastructure provisioning with Terraform and configuration management with Ansible. • Notebooks & Collaboration: Create and manage Jupyter Notebooks for experimentation and collaboration. • NVIDIA Integration: Integrate and optimize NVIDIA Enterprise Suite components (CUDA, NeMo Framework, Triton, TensorRT, GPU drivers) for accelerated computing. • MLOps Practices: Establish and maintain MLOps best practices for model lifecycle management, CI/CD, and monitoring (e.g., MLflow, Kubeflow). • Collaboration: Work closely with data scientists and platform engineers to ensure efficient resource utilization and scalability across environments.
Benefits
• Salary: Explicitly stated as part of the benefits. • Equity: Mentioned in the job posting and considered a benefit for eligible employees after one year with Ahead Technologies Pvt Ltd. • Paid Time Off (PTO): Included under paid time off, which is available to all full-time staff members as per company policy. The amount of leave granted depends on years of service but cannot be carried over from previous employers and must be used within the calendar year or forfeited. Employees are encouraged not to take more than 15 days in a month, with an annual cap at one week's pay per employee (excluding public holidays). • Insurance: Provided as part of Ahead Technologies Pvt Ltd.'s comprehensive health insurance plan. The company covers the full cost for all eligible employees and their dependents up to a specified limit, with an option to extend coverage at employee's expense (coinsurance). • Perks: Listed as part of Ahead Technologies Pvt Ltd.'s comprehensive benefits package which includes medical insurance, dental care for the company plus one additional person per family member and vision cover. Employees also receive a monthly stipend to purchase their own personal healthcare plan if they choose not to opt into these provided plans or wish to supplement them with other private coverage options (coinsurance). • Remote Work Options: Mentioned as an option for eligible employees after one year of service, subject to approval by the manager and compliance with company policies.
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