Senior Software Engineer, Machine Learning Inference Platform

Stack AV • Pittsburgh, PA

15h

About The Position

In the Senior Engineer role, you will own meaningful subsystems of Stack AV's inference platform and drive them from design through production. You will be the go-to engineer for one or more areas such as model onboarding, serving APIs, metering, observability, performance optimization, or tenant isolation. The role requires strong hands-on implementation, production debugging, thoughtful design, and the ability to mentor engineers while keeping delivery moving.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 4+ years of experience building and operating backend distributed systems end to end.
• Strong Data & ML systems fundamentals: data-intensive distributed systems, concurrency, networking and performance profiling.
• Hands-on experience with 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.
• Strong analytical and problem-solving skills.

Nice To Haves

• Autonomous vehicles (AV) experience is a bonus.

Responsibilities

• Own technical design and delivery of subsystems in a high-throughput, low-latency inference platform capable of handling multi-tenant, enterprise-grade inference workloads.
• 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.
• Decompose ambiguous work, drive issues to closure, and raise the engineering bar through code quality, reviews, testing, and mentoring.

What This Job Offers

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