
Ai Solutions Architect
2 weeks ago
IXL Cloud enables businesses, start-ups, researchers, and developers to train, deploy, and scale their AI systems with unmatched performance and flexibility.
**Your Responsibilities**:
- **Client Onboarding**: Guide new customers through setup and onboarding—provisioning environments, installing dependencies, and optimizing for their frameworks (e.g. PyTorch, TensorFlow, JAX).
- **Architect ML Workflows**: Collaborate with client teams to design scalable, fault-tolerant training and inference pipelines using IXL Cloud’s platform.
- **GPU Optimization**: Help clients choose the right compute resources (e.g. A100s vs. H100s, multi-GPU, MIG), batch sizes, and parallelism strategies to maximize throughput and cost-efficiency.
- **AI Stack Integration**: Support integration with tools like Hugging Face, Weights & Biases, Ray, Triton, LangChain, or vector databases.
- **Problem Solving**: Troubleshoot performance issues, networking bottlenecks, and environment-related bugs.
- **Feedback Loop**: Capture client needs and turn them into actionable feedback for our product and engineering teams.
- **Technical Enablement**: Build reusable templates, best practices, reference architectures, and documentation for common AI use cases (fine-tuning, retrieval-augmented generation, etc.).
It will be good to have:
- 5+ years in ML infrastructure, cloud architecture, or solutions engineering roles.
- Strong understanding of ML frameworks (PyTorch, TensorFlow), model training workflows, and deployment lifecycles.
- Experience working with NVIDIA systems
- Hands-on experience with GPU clusters, distributed training (e.g. DDP, Horovod), and containerized environments (Docker, Kubernetes).
- Client-facing experience and ability to communicate technical concepts clearly to diverse audiences.
- Familiarity with Python, bash scripting, and cloud compute orchestration (Terraform, Helm, etc.).
- Experience supporting real-world LLM, vision, or multi-modal workloads is a plus.
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