Wizardcommerce

Senior Machine Learning Engineer (Inference Platform)

Remote - USA · Senior

Sponsorship not specifiedDetected 48 days ago

PythonAWSGCPAzureCloud PlatformsCI/CDDevOpsPlatform EngineeringMachine LearningData ScienceLLMsMLOpsA/B TestingLeadership

About the role

This is not a traditional MLOps role focused solely on pipelines and tooling.
You'll be responsible for the inference infrastructure powering a live conversational shopping agent, operating multiple specialized serving engines under real-world production load.

Own and evolve our multi-engine inference platform, supporting a variety of model types and serving requirements.
Build and improve production ML pipelines - taking models from experimentation to reliable, high-throughput serving.
Define and implement model versioning, rollout, rollback, and lifecycle management strategies that ensure reproducibility and operational reliability.
Build observability, monitoring, alerting, and operational tooling for production inference systems.
Optimize inference performance through efficient resource utilization, hardware-aware serving strategies, and cost-conscious infrastructure design.
Partner with ML, Data, Product, and DevOps teams to turn ideas into production systems, driving the technical decisions on serving and scale.

Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field, or equivalent practical experience.
5-8+ years of experience in Software Engineering, ML Engineering, Platform Engineering, or Infrastructure Engineering, with direct ownership of production ML serving systems.
Hands-on experience running an LLM serving engine (vLLM, TGI, TensorRT-LLM, or SGLang) in production under real load - not just managed or hosted endpoints.
Experience with cloud platforms such as AWS, GCP, or Azure, and familiarity with ML lifecycle tooling, experimentation platforms, and model registries.
Experience serving heterogeneous workloads, including LLMs, embedding models, and extraction models, each with distinct latency, throughput, and scaling requirements.
Demonstrated ability to balance latency, throughput, reliability, and infrastructure cost while operating production-scale ML systems.
Experience in high-growth startup environments and comfort operating in fast-moving, evolving technical landscapes.

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