• Act as a liaison between end-users/clients and the IT department • Review, analyze, and evaluate complex business systems • Write detailed descriptions of user needs and program functions • Interview end-users/customers to define business requirements • Translate business requirements into functional specifications • Facilitate design sessions with business and technical resources • Develop project plans and prioritize project tasks • Perform quality control checks on software before release

Role Description SkyPilot exists because GPUs are scarce, expensive, and scattered — and the workloads that need them (pre-training, post-training, RL, high-throughput inference) push hardware to its limits. We're looking for an engineer to own the GPU and ML-systems layer that frontier AI teams run on: - Accelerator scheduling and utilization - The serving path - The integrations that make SkyPilot the fastest, most cost-efficient place to run demanding AI workloads A few points of GPU utilization here can save a team millions in compute and days on every training run. What you'll do - Own GPU scheduling, utilization and health: - How SkyPilot discovers, packs, and binpacks accelerator capacity across clouds and Kubernetes - Real-time GPU health monitoring and automatic failure recovery - Build optimizations for training and serving: - Enable large scale pre-training with node hot-swapping - Design storage systems for fast model checkpointing - Container migration, inference autoscaling and multi-cluster serving - Preemption handling and sandboxes for training, RL rollouts, and evals - Make the AI stack run great out of the box: - Deepen integrations with vLLM, PyTorch, Slime, and the frameworks teams use for pre-training and high-throughput inference Qualifications - Hands-on experience with GPU or accelerator systems and with ML training or inference infrastructure - Strong Python, and comfort reaching into systems-level and GPU-adjacent details - You care about squeezing most from the compute available to you - Experience operating large-scale training or high-throughput inference in production Requirements - Familiarity with the modern ML ecosystem (e.g. vLLM, PyTorch, CUDA, verl/slime) and workload-orchestration frameworks (e.g. Kueue, KAI, KServe) - You've done real ML-systems performance work - tell us about a bottleneck you hunted down (a stalled data pipeline, GPUs idling on a scheduling gap, communication you overlapped with compute) and what you measured before and after Benefits - Competitive compensation and equity - Comprehensive medical, dental, vision coverage for you and your dependents - The chance to work with some of the best minds in cloud, distributed, and AI systems — with significant autonomy and ownership - A front-row seat at the latest open-source infra startup from Berkeley (lineage: Databricks, Anyscale) - Gourmet lunch & dinner for the team to do their best work Company Description SkyPilot accelerates the world's most ambitious AI teams. Every hour they spend fighting infrastructure is an hour the frontier doesn't move — so SkyPilot turns fragmented compute across clusters into one optimized, highly available and easy-to-use pool: a single "AI supercomputer." SkyPilot (10k+ GitHub stars, 14M+ downloads) is deployed at 100s of companies — from Fortune 500s to top AI-natives like Abridge, Applied Compute, Mistral, Unconventional AI, H Company, and Nubank — with usage growing exponentially. Born in the UC Berkeley lab behind Spark and Databricks, our growing team includes top-tier talent from Databricks, Google, Berkeley, MIT, CMU, and Cornell.

Role Description - Pre-sales - assist in qualifying sales leads from a technical standpoint. - Effectively carry out presales function in solution offerings (proposal, demo, presentation, etc.). - Lead all technical aspects of a sales cycle with the customer, from the initial RFIs, through to RFPs & RFQs when required. - Actively participate in preparing tender documents and proposals, RFPs, RFIs and POC demo. - Sales calls - be the main technical resource on sales calls and answer/educate the customer on issues ranging from features, specifications and functionality to integration. - Conversant with networking applications and solutions. - Understudy customer requirements, environment and challenges and able to propose/provide security solution design and implementation solutions to clients. - Post-sales - be the lead technical contact for identified accounts for technical issues and will work closely with the technical support team and engineering to answer, elevate and resolve customer's technical issues. Qualifications - Field sales experience. - Experience in technical/pre-sales support as a sales or systems engineer. - Experience in LAN/WAN/Internet services administration. - Experience in handling mid and large enterprise accounts, lab setup and proof-of-concept (POC). - Solid understanding in security solutions implemented in Cloud environments such as AWS, Azure, Alibaba, Google Cloud, etc. - Knowledge on SaaS solutions, orchestration or multi-vendor integrated deployment. - Experience in Cybersecurity Frameworks like NIST, MITRE ATT&CK, OWASP, Cyber Kill Chain. - Exceptional skillset in networking/security solutions, such as Routing, Switching, VPN, Firewall, SDWAN, Sandboxing, UEBA, application security, SASE, ZTNA, EDR. - Solid understanding in the following technologies and protocols: RADIUS, PKI, IKE, Certificates, L2TP, IPSEC, FIREWALL, 802.1Q, MD5, SSH, SSL, SHA1, DES, 3DES. - Experience with encryption and authentication technologies required. - Exceptional presentation skills. Company Description Fortinet (NASDAQ: FTNT) secures the largest enterprise, service provider, and government organizations around the world. Fortinet empowers its customers with intelligent, seamless protection across the expanding attack surface and the power to take on ever-increasing performance requirements of the borderless network - today and into the future. Only the Fortinet Security Fabric architecture can deliver security without compromise to address the most critical security challenges, whether in networked, application, cloud or mobile environments. Fortinet ranks number one in the most security appliances shipped worldwide and more than 500,000 customers trust Fortinet to protect their businesses. We are committed to providing reasonable accommodations for all qualified individuals with disabilities. If you require assistance or accommodation due to a disability, please contact us at accommodations@fortinet.com. Fortinet is an equal opportunity employer. We value diversity in our company, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, military/veteran status or any other applicable legally protected characteristics in the location in which the candidate is applying.

• Lead toolchain, build, code-health, and performance-workflow adoption projects across large software components. • Evaluate and deploy supported GCC and LLVM/Clang toolchains, compiler options, linkers, sysroots, and cross-compilation configurations. • Integrate modern toolchains and workflows into complex build systems and continuous-integration environments. • Establish useful Clang diagnostic builds and targeted sanitizer coverage in partnership with component owners. • Evaluate techniques such as link-time optimization, profile-guided optimization, AutoFDO, and BOLT on representative software. • Use profiling, PMU data, flamegraphs, and binary/source analysis to identify actionable performance and code-quality findings. • Build automation, wrappers, validation scripts, dashboards, and migration helpers where they improve adoption and repeatability. • Measure changes in runtime, code size, build time, launch latency, throughput, quality, or engineering velocity. • Drive complex blockers to the appropriate compiler, runtime, library, infrastructure, or component owner. • Document validated approaches as reusable playbooks for other engineering teams. • Communicate technical results and tradeoffs clearly to engineers and leadership.