AI Inference Engineer

Evergrid; New York (NY); Hybrid; USD 140,000 - 160,000; Full time

Benefits offered by this job

Health insurance

Paid time off and holidays

Home office stipend

Job summary

Evergrid seeks a hands-on engineer to architect, build, and deploy high-scale production inference systems on Evergrid's infrastructure. You will own customer projects end to end, from exploration to production deployment and monitoring, embedding with customer teams and collaborating with platform groups.

Ideal candidates have 3+ years of engineering, strong Python skills, and familiarity with AI/ML lifecycles.

Qualifications

• Requires a degree in CS/Engineering/Math or equivalent experience.
• 3+ years of professional engineering experience.
• Experience with SGLang, vLLM, and other inference engines and schedulers.
• Strong production software skills, preferably in Python.
• Familiarity with the AI/ML lifecycle: model development, deployment, monitoring.
• Excellent communication on complex topics.
• Experience building or optimizing AI/ML systems is valued.
• Comfort working directly with customers and owning outcomes end to end.

Responsibilities

• Architect, build, and deploy high-scale production inference systems.
• Own customer projects end to end from exploration to production deployment and monitoring.
• Collaborate with customer engineering teams and Evergrid platform teams.
• Turn unclear goals into well-scoped PoCs and technical specs.
• Optimize inference pipelines for latency, throughput, reliability, and cost.
• Improve Evergrid's inference stack, tooling, and platform.
• Drive customer-facing initiatives and ownership of outcomes.

Skills

3+ years professional software eng

Python production software

Clear communication

AI/ML lifecycle familiarity

Customer-facing experience

Education

Bachelor's, Master's, or PhD in CS/Engineering/Mathematics

Tools

Python

SGLang

vLLM

inference engines

schedulers

Job description

United States | Hybrid or Remote | Full-time

The role

You'll work directly with Evergrid's customers to architect, build, and deploy high-scale production inference systems on our infrastructure.

You own customer projects end to end, from early exploration to production deployment and monitoring. You take goals that start out unclear and turn them into reliable services you can monitor, with defined quality, latency, and cost targets. This role is hands-on. It combines software development, inference performance engineering, and customer-facing execution. You'll embed with customer engineering teams and work closely with our platform and infrastructure teams.

What you own

• Production-grade software systems and inference services, built mainly in Python.

• Customer engagements end to end: problem framing, evaluation, proof of concept, production deployment, and monitoring.

• Direct work with customer engineering teams through sales, implementation, and expansion.

• Turning unclear goals into clear technical specs and well-scoped PoCs.

• Inference pipelines optimized for latency, throughput, reliability, and cost.

• Improvements to Evergrid's inference stack, tooling, and platform.

• Customer-facing initiatives, where you act as engineer, technical lead, and the person who drives execution.

• Sound tradeoffs under uncertainty that lead to simple, maintainable solutions.

What you bring

• A bachelor's, master's, or PhD in Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience.

• 3+ years of professional engineering experience.

• Experience with SGLang, vLLM, and other inference engines and schedulers.

• Strong production software skills, preferably in Python.

• Familiarity with the AI/ML lifecycle: model development, deployment, and monitoring.

• Clear communication on complex technical topics.

• Experience building, deploying, or optimizing AI/ML systems, which we value highly.

• Comfort working directly with customers and owning outcomes end to end.

Benefits & Compensation

• Compensation: $140,000 - $160,000

• Health insurance

• Paid time off and paid holidays

• Home office stipend