Staff Software Engineer, Machine Learning Inference Platform

Stack AV • Pittsburgh, PA

4h

About The Position

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. 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.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 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: 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 (TensorRT, vLLM, etc) or serving frameworks (Dynamo, Triton or equivalent).
• Strong programming skills in C++, Go, Rust or Python.
• Familiarity with deep learning frameworks (PyTorch, etc.) as well as 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.
• Excellent verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.

Nice To Haves

• Autonomous vehicles (AV) experience is a bonus.

Responsibilities

• Design platform architecture for multi-tenant inference workloads across 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 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 their own work but also set a culture of engineering excellence within the team.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior