Senior ML Infrastructure Engineer – Production Inference Platform

Unity; Washington; Híbrido; USD 187.000 - 243.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Health insurance

Stock ownership

Retirement plan

Vacation days

Parental leave support

Commuter subsidy

Descripción de la vacante

Unity is seeking a Senior ML Engineer to design and evolve Unity Vector's online model inference platform, building reliable infrastructure for serving ML models in production and optimizing inference performance across high-traffic systems.

You will collaborate with ML engineers, platform teams, and product stakeholders to ensure models can be deployed, scaled, monitored, and iterated efficiently, shaping packaging, serving, validation, monitoring, and optimization in production.

Formación

• Experience building and operating production-grade online ML inference systems.
• Experience with model serving frameworks such as Triton Inference Server, TorchServe, Ray Serve, TensorFlow Serving, or similar systems.
• Strong experience with distributed systems, Kubernetes, autoscaling, service reliability, and production observability.
• Strong programming skills in Python, with practical experience working on production ML systems and high-scale services.
• Experience with PyTorch and modern model deployment workflows, including model packaging, validation, and serving lifecycle management.
• Experience designing infrastructure for safe model rollout, canary testing, A/B experimentation, and automated rollback.
• Strong systems thinking, with the ability to reason about latency, throughput, reliability, scalability, and cost tradeoffs in online systems.
• Proven ability to lead technical direction and influence architectural decisions across teams without formal authority.

Responsabilidades

• Design and operate large-scale online inference infrastructure that serves production ML models with low latency and high reliability.
• Develop infrastructure that supports distributed training workflows.
• Integrate ML pipelines with workflow orchestration systems for reliable multi-stage training workflows.
• Optimize model performance through compilation, GPU/CPU utilization improvements, and runtime tuning.
• Improve observability of ML systems through latency, throughput, error-rate, cost, and model-health monitoring.
• Partner with ML engineers to support faster model iteration while maintaining safety and cost efficiency.
• Improve the reliability and reproducibility of model serving workflows, including packaging, validation, and deployment automation.
• Lead architectural improvements to make the online ML platform robust, scalable, and cost-efficient.

Conocimientos

Production ML infra

Python

Kubernetes

Distributed systems

Model deployment

Herramientas

Triton Inference Server

Ray

Flyte

Descripción del empleo

Unity is seeking a Senior ML Engineer to design and evolve Unity Vector's online model inference platform, building reliable infrastructure for serving ML models in production and optimizing inference performance across high-traffic systems.

You will collaborate with ML engineers, platform teams, and product stakeholders to ensure models can be deployed, scaled, monitored, and iterated efficiently, shaping packaging, serving, validation, monitoring, and optimization in production.