Note: The job is a remote job and is open to candidates in USA. Stack AV is developing revolutionary AI and advanced autonomous systems designed to enhance safety, reliability, and efficiency in the trucking transportation industry. In the Senior Software Engineer role, you will own meaningful subsystems of the inference platform, driving them from design through production while mentoring other engineers and ensuring timely delivery.

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

Skills

• 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
• Autonomous vehicles (AV) experience is a bonus

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