• Collaborate with Tech Leaders, Architects and other Engineers to develop solutions for complex problems in distributed computing and infrastructure management. • Automate solutions for operational issues, such as monitoring, performance, planning, and disaster response. • Participate in an on-call rotation to support our business-critical infrastructure. • Ensure a high quality implementation by applying Infrastructure as Code industry standards. • Demonstrate effective communication by authoring and reviewing design documents, runbooks, and other service documentation, and keeping a good record of changes in the systems. • Apply Agile methodologies to continuously deliver value to the customers. • Act as point of contact for legacy/new Compute system components.

Role Description We are seeking an ML Infrastructure Engineer to design, build, and operate the platform layer that powers large-scale AI training and inference workloads. The role focuses on: - GPU clusters - Distributed training frameworks - Scheduling - Storage performance - Developer experience for ML engineers and researchers The ideal candidate has built or operated production AI infrastructure at scale, understands the interaction between hardware, kernel, scheduler, and ML framework, and brings strong software engineering discipline to platform work. Qualifications - Bachelor’s or Master’s degree in Computer Science or a related field. - Six or more years of experience in infrastructure, platform, or HPC engineering. - Hands-on experience operating GPU clusters or large-scale ML training infrastructure. - Strong proficiency in Python and at least one systems language such as Go or C++. - Deep understanding of distributed training, accelerator architectures, and collective communication. - Experience with Kubernetes, Slurm, Ray, or similar scheduling systems for ML workloads. - Strong understanding of Linux internals, networking, and high-performance storage. - Experience with at least one major cloud provider’s ML infrastructure offerings. - Strong software engineering practices including testing, CI/CD, and code review. - Excellent communication and cross-functional collaboration skills. Requirements - Design and operate GPU and accelerator infrastructure for training and inference, spanning on-prem clusters, cloud-managed services, and hybrid configurations. - Build scheduling, queueing, and resource-sharing systems that maximize accelerator utilization across many teams. - Integrate frameworks such as PyTorch, JAX, DeepSpeed, FSDP, Megatron-LM, and Ray Train into a unified platform offering. - Operate high-performance storage systems and data pipelines that keep accelerators fed with training data at near-line-rate. - Design networking architectures supporting RDMA, InfiniBand, NCCL, and high-bandwidth collective communication. - Build observability for AI workloads including utilization, throughput, training stability, and failure-mode analytics. - Implement checkpointing, restart, and fault-tolerance patterns for long-running training jobs at scale. - Drive cost optimization across compute, storage, and networking through scheduling, spot capacity, and right-sizing. - Develop developer tooling and paved-road workflows that let researchers launch experiments safely and efficiently. - Partner with research and applied ML teams to plan capacity for upcoming training runs. - Implement security controls, isolation, and access management for multi-tenant AI infrastructure. - Drive automation across cluster provisioning, lifecycle management, and configuration enforcement. - Maintain runbooks, capacity dashboards, and operational documentation for the AI platform. - Stay current with AI infrastructure research, accelerator hardware, and emerging open-source AI tooling. Benefits - 100% remote, full-time, direct W2 position with Bright Vision Technologies. - Support for H1B transfers for qualified candidates. - Tremendous career growth potential.

• Act as a proactive technical reference, influencing architectural decisions and fostering a DevOps culture across multiple development teams. • Architect, manage, and operate AWS/GCP services, ensuring seamless interoperability between platforms with Cross Connects and VPNs. • Design and provision scalable infrastructure for development teams using Terraform / Terragrunt and GitLab pipelines. • Drive investigations to optimise cloud costs through traffic analysis and CloudTrail optimization. • Drive AWS Organization account onboarding and enforce security best practices.

Role Description We are seeking an Infrastructure Automation Engineer who blends strong Python development skills with deep networking domain expertise to automate network configuration, change management, and observability across multi-vendor enterprise networks. The role focuses on building production-grade automation using modern network APIs, infrastructure-as-code, and CI/CD practices that bring software engineering discipline to network operations. The ideal candidate writes idiomatic Python, has shipped network automation in production, and combines networking depth with practical software-engineering rigor. In this role, you will work closely with cross-functional partners — product, design, engineering, operations, and business stakeholders — to translate ambiguous requirements into well-engineered solutions, and will be expected to raise the bar through code review, design review, and mentorship of more junior engineers. The successful candidate brings strong engineering discipline, a clear communication style, and a track record of shipping meaningful work that holds up well in production. Key Responsibilities - Design and develop network automation solutions in Python using Netmiko, Nornir, NAPALM, and Scrapli. - Build automation pipelines for configuration management, deployment, and validation across multi-vendor environments. - Develop integrations with network APIs including NETCONF, RESTCONF, gNMI, and vendor-specific APIs. - Implement source-of-truth platforms such as NetBox or Nautobot and drive automation from authoritative data. - Build infrastructure-as-code for network configuration using Ansible, Terraform, and Jinja2 templating. - Implement network testing and validation using pyATS, Genie, Batfish, and Suzieq. - Develop CI/CD pipelines for network changes including pre-deployment validation and rollback. - Build observability and telemetry pipelines using gNMI, streaming telemetry, and modern analytics platforms. - Implement intent-based networking patterns and self-healing network workflows that let the network express desired state declaratively and converge toward it automatically when drift or failures occur. - Automate compliance and audit workflows across the network estate, generating evidence on demand and continuously verifying that network configuration matches the policies the organization has committed to. - Partner with network engineering teams to identify and automate high-impact manual workflows. - Develop reusable libraries, frameworks, and abstractions adopted across multiple automation efforts. - Mentor network engineers on Python development, software engineering practices, and modern automation patterns. - Stay current with network automation tooling, vendor API evolution, and broader industry developments. Qualifications - Bachelor’s degree in Computer Science, Networking, or a related field. - Five or more years of network automation experience. - Strong Python development skills including OOP, testing, and packaging. - Deep networking fundamentals including routing, switching, and BGP. - Hands-on experience with Netmiko, NAPALM, Nornir, or Scrapli. - Experience with modern network APIs (NETCONF, RESTCONF, gNMI). - Strong experience with Ansible and Jinja2 templating for network automation. - Familiarity with NetBox, Nautobot, or other source-of-truth platforms. - Strong Git-based workflows and CI/CD experience. - Excellent communication and collaboration skills. Preferred Qualifications - Cisco DevNet or vendor automation certifications. - Experience with multi-vendor networks (Cisco, Arista, Juniper). - Familiarity with streaming telemetry and modern observability stacks. - Open-source contributions to network automation projects. - Experience with cloud networking automation in addition to on-premises. How to Apply Would you like to know more about this opportunity? For immediate consideration, please send your resume to [email protected] or contact us at (908) 505-3544. Learn more about Bright Vision Technologies at www.bvteck.com .