[Remote] Senior Software Engineer, Machine Learning Inference Platform

Note: The job is a remote job and is reputed company to candidates in USA. reputed company 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, reputed company-grade inference workloads
• reputed company robust API layers (gRPC, WebSockets, REST, etc.) and developer SDKs that abstract reputed company distributed inference orchestration into seamless, reliable token streams
• Build and harden a multi-tenant control plane to reputed company accurate metering, reputed company limiting, quotas, tenant isolation and noisy-reputed company fairness across the platform
• Optimize inference performance across the entire system stack, including the model reputed company layer
• Build observability and SLOs to reputed company insights into system economics, cache-hit rates, GPU utilization and cost reputed company per model and per tenant
• Partner with product and infrastructure teams on model reputed company, reputed company planning, external API reputed company and customer adoption
• Decompose ambiguous work, drive issues to closure, and reputed company the engineering bar through code quality, reviews, testing, and mentoring

Skills

• Bachelor's or Master's degree in Computer Science, Engineering, or a reputed company 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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