<div class="content-intro">About Stack: Stack is developing revolutionary AI and advanced autonomous systems designed to enhance safety, reliability, and efficiency of modern operations. Stack's autonomous technology incorporates cutting-edge advancements in artificial intelligence, robotics, machine learning, and cloud technologies, empowering us to create innovative solutions that address the needs and challenges of the dynamic trucking transportation industry. With decades of experience creating and deploying real world systems for demanding environments, the Stack team is dedicated to developing an autonomous solution ecosystem tailored to the trucking industry's unique demands.</div>About the Role: In the Staff Engineer role, you will define and drive architecture for a high-throughput, low-latency, multi-tenant ML inference platform. You will balance hands-on coding with long-term technical direction, operate across ML Platform, infrastructure, MLE, and external-facing API needs, and establish principled architecture for serving, control plane, observability, capacity, tenant isolation, system economics, and model-engine integration. Responsibilities: <ul> <li>Design platform architecture for multi-tenant inference workloads across serving, orchestration, control plane, APIs, SDKs, observability, and model-engine integration.</li> <li>Develop robust API layers (gRPC, WebSockets, REST, etc.) and developer SDKs that abstract complex distributed inference orchestration into seamless, reliable token streams.</li> <li>Build and harden a multi-tenant control plane to enable accurate metering, rate limiting, quotas, tenant isolation and noisy-neighbor fairness across the platform. </li> <li>Optimize inference performance across the entire system stack, including the model engine layer. </li> <li>Build observability and SLOs to gain insights into system economics, cache-hit rates, GPU utilization and cost accounting per model and per tenant.</li> <li>Partner with product and infrastructure teams on model onboarding, capacity planning, external API contracts and customer adoption. </li> <li>Promote Engineering Excellence: Maintain a high bar for engineering excellence in their own work but also set a culture of engineering excellence within the team.</li> </ul> Qualifications:  <ul> <li>Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.</li> <li>Experience: 7+ years of experience building and operating backend distributed systems end to end.</li> <li>Demonstrated cross-team technical leadership in backend distributed systems, ML infrastructure, inference serving, or high-performance compute platforms.</li> <li>Strong Data & ML systems fundamentals: data-intensive distributed systems, concurrency, networking and performance profiling.</li> <li>Hands-on experience running large-scale inference services on GPUs, including KV caches, prefill/decode stages and throughput/latency trade-offs.</li> <li>Direct experience with inference engines (TensorRT, vLLM, etc) or serving frameworks (Dynamo, Triton or equivalent).  </li> <li>Technical Skills: <ul> <li>Strong programming skills in C++, Go, Rust or Python.</li> <li>Familiarity with deep learning frameworks (PyTorch, etc.) as well as model parallelism. </li> <li>Familiarity with GPU computing primitives such as CUDA, NCCL, NVLink, and hardware-specific optimizations.</li> <li>Practical understanding of high-performance networking architectures, including InfiniBand, RoCE, and low-latency cluster communication.</li> </ul> </li> <li>Communication: Excellent verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.</li> <li>Autonomous vehicles (AV) experience is a bonus.</li> </ul><div class="content-conclusion">We are proud to be an equal opportunity workplace. We believe that diverse teams produce the best ideas and outcomes. We are committed to building a culture of inclusion, entrepreneurship, and innovation across gender, race, age, sexual orientation, religion, disability, and identity. Check out our <a href="https://stackav.com/join/policy">Privacy Policy.</a> Please Note: Pursuant to its business activities and use of technology, Stack AV complies with all applicable U.S. national security laws, regulations, and administrative requirements, which can restrict Stack AV’s ability to employ certain persons in certain positions pursuant to a range of national security-related requirements. As such, this position may be contingent upon Stack AV verifying a candidate’s residence, U.S. person status, and/or citizenship status. This position may also involve working with software and technologies subject to U.S. export control regulations. Under these regulations, it may be necessary for Stack AV to obtain a U.S. government export license prior to releasing its technologies to certain persons. If Stack AV determines that a candidate’s residence, U.S. person status, and/or citizenship status will require a license, prohibit the candidate from working in this position, or otherwise be subject to national security-related restrictions, Stack AV expressly reserves the right to either consider the candidate for a different position that is not subject to such restrictions, on whatever terms and conditions Stack AV shall establish in its sole discretion, or, in the alternative, decline to move forward with the candidate’s application.</div>

Staff Software Engineer, Machine Learning Inference Platform

DESCRIPTION

REQUIRED SKILLS