Stack AV
Technology
SeniorSoftwareEngineer,MachineLearningInferencePlatform
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Software Engineer, Machine Learning Inference Platform at Stack AV. Skills: Machine Learning Inference, Distributed systems, Backend development. Own technical design and delivery of subsystems. Develop robust API layers”
Industry & Context.
Analytical skills; Problem-solving skills
What They're Looking For.
Must Have
4+ years of experience building and operating backend distributed systems, Data & ML systems fundamentals, Hands-on experience with large-scale inference services on GPUs, Direct experience with inference engines or serving frameworks
Nice to Have
Autonomous vehicles (AV) experience is a bonus
What You'll Do.
Own technical design and delivery of subsystems
Develop robust API layers
Develop developer SDKs
Build multi-tenant control plane
Optimize inference performance
Build observability and SLOs
Partner with product teams
Partner with infrastructure teams
Decompose ambiguous work
Drive issues to closure
Raise engineering bar
How You'll Work.
Team & Collaboration
Partner with product teams; Partner with infrastructure teams
Process & Methodology
Technical design
Full Job Description
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 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. 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 pla
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