✨ AI Insights & Summary
Stack is revolutionizing the trucking industry with AI-driven autonomous systems, and this Staff Engineer role is pivotal in building the core ML inference platform. This is a unique opportunity for a seasoned backend distributed systems expert to define and drive the architecture of a high-throughput, low-latency, multi-tenant platform. If you thrive on complex system design, have deep expertise in ML infrastructure, and are passionate about shaping the future of autonomous technology, this role offers significant impact and growth potential.
Staff Engineer, ML Inference Platform
About Stack
Stack is developing revolutionary AI and advanced autonomous systems designed to enhance the safety, reliability, and efficiency of modern operations. Our technology integrates cutting-edge advancements in artificial intelligence, robotics, machine learning, and cloud technologies to create innovative solutions for the dynamic trucking transportation industry. With decades of experience deploying real-world systems in demanding environments, the Stack team is dedicated to building an autonomous solution ecosystem tailored to the trucking industry's unique demands.
About the Role
In the Staff Engineer role, you will define and drive the architecture for a high-throughput, low-latency, multi-tenant Machine Learning (ML) inference platform. You will balance hands-on coding with long-term technical direction, operating across ML Platform, infrastructure, MLE, and external-facing API needs. Your focus will be on establishing principled architecture for serving, control plane, observability, capacity, tenant isolation, system economics, and model-engine integration.
Responsibilities
- Design platform architecture for multi-tenant inference workloads, encompassing serving, orchestration, control plane, APIs, SDKs, observability, and model-engine integration.
- Develop robust API layers (gRPC, WebSockets, REST, etc.) and developer SDKs that abstract complex distributed inference orchestration into seamless, reliable token streams.
- Build and harden a multi-tenant control plane to enable accurate metering, rate limiting, quotas, tenant isolation, and noisy-neighbor fairness across the platform.
- Optimize inference performance across the entire system stack, including the model engine layer.
- Build observability and Service Level Objectives (SLOs) to gain insights into system economics, cache-hit rates, GPU utilization, and cost accounting per model and per tenant.
- Partner with product and infrastructure teams on model onboarding, capacity planning, external API contracts, and customer adoption.
- Promote Engineering Excellence: Maintain a high bar for engineering excellence in your own work and set a culture of engineering excellence within the team.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- Experience: 7+ years of experience building and operating backend distributed systems end-to-end.
- Demonstrated cross-team technical leadership in backend distributed systems, ML infrastructure, inference serving, or high-performance compute platforms.
- Strong Data & ML systems fundamentals, including data-intensive distributed systems, concurrency, networking, and performance profiling.
- Hands-on experience running large-scale inference services on GPUs, including KV caches, prefill/decode stages, and throughput/latency trade-offs.
- Direct experience with inference engines (e.g., TensorRT, vLLM) or serving frameworks (e.g., Dynamo, Triton, or equivalent).
- Technical Skills:
- Strong programming skills in C++, Go, Rust, or Python.
- Familiarity with deep learning frameworks (e.g., PyTorch) and model parallelism.
- Familiarity with GPU computing primitives such as CUDA, NCCL, NVLink, and hardware-specific optimizations.
- Practical understanding of high-performance networking architectures, including InfiniBand, RoCE, and low-latency cluster communication.
- Communication: Excellent verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.
- Autonomous vehicles (AV) experience is a bonus.
Equal Opportunity & Compliance
Stack is proud to be an equal opportunity workplace committed to building a culture of inclusion, entrepreneurship, and innovation. We believe diverse teams produce the best ideas and outcomes. We comply with all applicable U.S. national security laws, regulations, and administrative requirements, which may restrict employment for certain individuals. This position may be contingent upon verification of residence, U.S. person status, and/or citizenship status, and may involve working with technologies subject to U.S. export control regulations. Stack AV reserves the right to consider candidates for different positions or decline to move forward based on these requirements.