Senior ML Infra Backend Engineer – Streaming Platform

Philo; San Francisco (CA); On-site; USD 170,000 - 250,000; Full time

Job summary

Philo is seeking an enthusiastic Infrastructure MLOps Software Engineer to help build and improve ML infrastructure across the company. You’ll contribute to serving models for real-time recommendations and LLM workloads, while advancing our cloud-based platform and observability.

The role emphasizes scalable infrastructure, GPU/accelerator management on Kubernetes, and close collaboration with engineering teams to ship reliable ML systems. Philo values pragmatism and collaboration.

Qualifications

• 8+ years of software and infrastructure experience.
• 4+ years building ML systems at scale (training and inference).
• Experience with distributed systems and microservices architecture.
• Linux and Docker environments proficiency.
• Cloud experience with AWS or GCP and services like CloudWatch, RDS, VPC.

Responsibilities

• Manage core Philo infrastructure focusing on ML/LLM workloads.
• Design, build, and maintain cloud components (AWS, Kubernetes).
• Scale model serving and inference infra for real-time recommendations and LLM workloads.
• Manage GPU and accelerator infra on Kubernetes; optimize costs.
• Build monitoring and observability for system health and model performance.
• Develop CI/CD pipelines to test and deploy code.
• Promote IaC practices and collaborate with other engineers.

Skills

8+ years exp

Distributed systems

Kubernetes

Golang

Cloud computing

Education

BS in CS or related

Tools

Docker

Terraform

Prometheus

MLflow

Job description

Philo is seeking an enthusiastic Infrastructure MLOps Software Engineer to help build and improve ML infrastructure across the company. You’ll contribute to serving models for real-time recommendations and LLM workloads, while advancing our cloud-based platform and observability.

The role emphasizes scalable infrastructure, GPU/accelerator management on Kubernetes, and close collaboration with engineering teams to ship reliable ML systems. Philo values pragmatism and collaboration.