Senior AI Model Serving Engineer – Equity

Sciforium; San Francisco (CA); On-site; USD 190,000 - 250,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

401(k) plan

Daily lunch, snacks, and beverages

Flexible time off

Competitive salary and equity

Job summary

Sciforium is seeking a Senior Software Engineer to help build the core model serving platform across C++, Python, runtime execution, and distributed infrastructure for real-time AI applications. You will work with ML researchers and systems engineers to deploy high-performance serving engines and optimize large AI models at scale.

You will gain hands-on experience with performance engineering, scalable ML/MLOps infrastructure, and a fast-moving, high-ownership team culture.

Qualifications

• Bachelor's degree (or equivalent) in CS/Engineering or related field.
• 3+ years in software engineering focusing on infrastructure or ML systems.
• Strong in C++, Python, Go, and Rust; experience with Kubernetes.

Responsibilities

• Build the model serving platform, including API, Control Plane, Billing, Monitoring, and distributed inference features.
• Collaborate with ML researchers to integrate new multimodal models into production workflows.
• Write reliable, maintainable code with strong testing and documentation practices.
• Provide operational support for keeping our production services highly performant, available and reliable.
• Help troubleshoot complex issues across runtime, service, and GPU layers, working closely with other engineers.

Skills

C++

Python

Go

Rust

Kubernetes

ML/MLOps

Education

Bachelor’s degree in CS or Engineering

Tools

Containerization

Job description

Sciforium is seeking a Senior Software Engineer to help build the core model serving platform across C++, Python, runtime execution, and distributed infrastructure for real-time AI applications. You will work with ML researchers and systems engineers to deploy high-performance serving engines and optimize large AI models at scale.

You will gain hands-on experience with performance engineering, scalable ML/MLOps infrastructure, and a fast-moving, high-ownership team culture.