AI Platform Engineer
通过将云基础设施，自动化和分析以及软件交付方面的进步结合在一起，我们帮助企业实现数字转型的承诺。在 AHEAD,我们优先创建一个属于人的文化，所有观点和声音都能被代表，重视，尊重和听到。我们创造空间让每个人都能够表达自己的想法，改变并推动 AHEAD 的文化。我们是平等机会的雇主，并不会根据一个人的种族，国家起源，颜色，性别，性别认同，性别表达，性取向，宗教，年龄，残疾，婚姻状况或任何其他受法律保护的特征进行歧视。无论实际还是被认为的。我们接受所有将为 AHEAD 多样化和丰富思想和观点做出贡献的候选人。我们正在寻找一名经验丰富的人工智能平台工程师来设计，部署和优化 AI/ML 基础设施，人工智能工作流程和自动管道。本角色重点是建立可扩展环境，用于训练和部署机器学习模型，利用现代管弦乐，自动化和 GPU 加速技术。你将与数据科学家和平台工程师合作，在云和混合环境中推动高效的资源利用和可扩展性操作。关键责任 · AI/ML:架构和管理基于 AI/ML 的工作负载的 Kubernetes 集群。· GPU Orchestration:实现 Run:ai 和运营商为 GPU 资源管弦乐和工作负载安排。· 自动化 & 管道：开发和维护基于 Python 的自动化脚本和 ML 管道；·笔记本和协作：创建和管理 Jupyter 笔记本书用于实验和合作。· NVIDIA 集成：整合并优化 NVIDIA 企业套件组件 （CUDA,NeMo Framework,Triton, TensorRT,GPU 驱动程序）为加速计算。· MLOps 实践：建立和维护 MLOps 最佳实践模型生命周期管理，CI/CD,监测 （例如 MLflow,Kubeflow）. ·协作：与数据科学家和平台工程师密切合作以确保高效的资源利用和可扩展性。需要技能和经验跨环境。· 强大的 Python 能力和 ML 框架 (TensorFlow, PyTorch) 的经验。·实践
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AHEAD builds platforms for digital business. By weaving together advances in cloud infrastructure, automation and analytics, and software delivery, we help enterprises deliver on the promise of digital transformation.
At AHEAD, we prioritize creating a culture of belonging, where all perspectives and voices are represented, valued, respected, and heard. We create spaces to empower everyone to speak up, make change, and drive the culture at AHEAD.
We are an equal opportunity employer, and do not discriminate based on an individual's race, national origin, color, gender, gender identity, gender expression, sexual orientation, religion, age, disability, marital status, or any other protected characteristic under applicable law, whether actual or perceived.
We embrace all candidates that will contribute to the diversification and enrichment of ideas and perspectives at AHEAD.
We are seeking an experienced AI Platform Engineer to design, deploy, and optimize AI/ML infrastructure, AI workflows, and automated pipelines. This role focuses on building scalable environments for training and deploying machine learning models, leveraging modern orchestration, automation, and GPU acceleration technologies. You will collaborate with data scientists and platform engineers to drive efficient resource utilization and scalable operations across cloud and hybrid environments.
Key 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.
Required Skills & Experience
- 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.
Qualifications
- 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).
Why AHEAD:
Through our daily work and internal groups like Moving Women AHEAD and RISE AHEAD, we value and benefit from diversity of people, ideas, experience, and everything in between.
We fuel growth by stacking our office with top-notch technologies in a multi-million-dollar lab, by encouraging cross department training and development, sponsoring certifications and credentials for continued learning.
India Employment Benefits include:
Comprehensive health insurance coverage for employees, with options to extend coverage to dependents
Paid time off and company holidays, along with additional leave benefits as per policy
Flexible work arrangements, supporting work-life balance
Learning and development opportunities to support continuous growth and upskilling
Employee wellness initiatives and programs focused on physical and mental well-being
Retirement and statutory benefits in line with India regulations
Inclusive and people-first culture, with a strong focus on collaboration and ownership
Originally posted on Himalayas