Stack AV

Staff Software Engineer, Machine Learning Inference Platform

Pittsburgh, PA or Remote · Staff+ · Contract

Sponsorship not specifiedDetected 37 days ago

GoRustC++Distributed SystemsRESTgRPCWebSocketsMachine LearningDeep LearningPyTorchAccountingLeadershipCommunication

About the role

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.

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.
Maintain a high bar for engineering excellence in their own work but also set a culture of engineering excellence within the team.
In the Staff Engineer role, you will define and drive architecture for a high-throughput, low-latency, multi-tenant ML inference platform.

Direct experience with inference engines (TensorRT, vLLM, etc) or serving frameworks (Dynamo, Triton or equivalent).
Communication: Excellent verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.
Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
Education: Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
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.
Technical Skills:
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.

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.
Autonomous vehicles (AV) experience is a bonus.
This position may also involve working with software and technologies subject to U.S. export control regulations.

As such, this position may be contingent upon Stack AV verifying a candidate's residence, U.S. person status, and/or citizenship status

This listing is sourced directly from Stack AV's careers page and normalized into a canonical job model.