Validate and troubleshoot InfiniBand and RoCE fabrics during GPU cluster bring-up and expansion.
Tune fabric performance parameters for distributed AI workloads such as NCCL and MPI.
Collaborate with GPU and networking teams to diagnose and resolve fabric-level issues and optimize performance.
Vultr makes high-performance cloud infrastructure easy to use and affordable for enterprises and AI innovators worldwide. With 33 global data centers and hundreds of thousands of customers, it is the largest privately-held cloud infrastructure company, offering a culture of innovation and growth.
Optimize production LLM serving with vLLM and SGLang to maximize throughput and minimize latency through batching and quantization.
Profile training runs to find bottlenecks and resolve them with attention implementations like FlashAttention on H200 and GB200 hardware.
Deploy and operate multiple models on shared GPU clusters with autoscaling, bin-packing, and efficient handling of mixed workloads.
Egen is a fast-growing technology company with a data-first mindset, partnering with clients on Google Cloud and Salesforce to drive action through data and insights. We are a team of dedicated engineers who thrive on solving tough problems and continually innovate to achieve fast, effective results.
Implement and maintain AI benchmarks using evaluation infrastructure like the Inspect library.
Contribute to the design and development of new benchmarks for frontier AI models.
Collaborate with researchers and engineers to ensure accurate and insightful evaluation data.
Epoch AI is a research institute investigating trends in machine learning and the economic consequences of AI. With a small, mission-driven team, we aim to provide rigorous, independent insights into AI development.
Lead engineering deployment, scaling, and operations of AI compute clusters with GPU fleets and bare metal environments.
Drive reliability, monitoring, automation, and incident response for AI infrastructure.
Collaborate with AI/ML, networking, and product teams to align infrastructure with business needs.
Our partner is a fast-growing cloud environment focused on building large-scale AI infrastructure. They seek a senior leader to manage engineering operations for advanced AI compute clusters.
Own performance optimization and reliability of large-scale GPU clusters and InfiniBand networking for HPC workloads.
Diagnose and resolve complex system-level issues across GPU, network, and compute layers, integrating new hardware components.
Develop automation for monitoring, fault detection, and proactive remediation in distributed compute environments.
Our partner is building a next-generation AI cloud infrastructure environment, focusing on large-scale high-performance computing systems. They foster a highly technical engineering culture with experts across systems, networking, and virtualization, offering career development and continuous learning opportunities.
Lead core infrastructure and SRE teams to ensure the highest reliability and performance for massive GPU computing demands.
Oversee HPC networking and distributed storage engine innovation to support massive multi-node AI workloads.
Build and scale a high-output engineering org while partnering cross-functionally with product and GTM leadership.
Runpod is the AI Developer Cloud, providing a platform for over one million developers to experiment, train, fine-tune, deploy, and scale AI. As a small, remote-first team that closed a $100M Series A, we move fast and take ownership seriously.
Own end-to-end technical execution for strategic customer and partner engagements, including discovery, infrastructure design, implementation, and production deployment.
Design and build cloud infrastructure supporting advanced AI workloads, including simulation, training, evaluation, inference, and large-scale batch processing.
Improve platform reliability, security, performance, and cost efficiency by debugging issues across application, network, storage, compute, and orchestration layers.
The partner company is building the infrastructure foundation for next-generation AI applications and physical AI workloads. The engineering team is pioneering and values ownership, technical excellence, and solving challenging engineering problems at scale.
Lead the design and operation of GPU infrastructure for AI workloads.
Manage Kubernetes-based environments and optimize for AI training and inference.
Define operational standards, implement monitoring, and collaborate with AI engineering teams.
ELEKS is a software engineering company that partners with enterprises to accelerate digital transformation. They have a global team of over 2,000 professionals and foster a culture of innovation and collaboration.
Participate in sales meetings, provide architectural recommendations, and build proof-of-concept solutions for onboarding high-spending customers.
Troubleshoot and resolve complex technical issues using code analysis, scripting, and log analysis.
Create and maintain technical documentation and deliver training sessions, webinars, and demos.
Runpod is the AI Developer Cloud, providing a platform for over one million developers to experiment, train, fine-tune, deploy, and scale AI. We are a small, remote-first team that takes ownership seriously, moves fast, and ships work relied on by more than a million developers daily.
Build and operate production-grade model serving infrastructure using vLLM, TGI, or Triton frameworks.
Design and implement auto-scaling, multi-model architectures, and intelligent request routing for ML inference.
Optimize GPU utilization, memory efficiency, and observability to ensure low-latency, cost-effective systems.
They are a distributed cloud infrastructure startup building AI-native cloud services with GPU-powered compute. The company is well-funded, fast-scaling, and operates in a remote-first environment with a focus on sustainability and decentralization.