Machine Learning Infrastructure Engineer

Bright Vision Technologies; United States; Remote; USD 105,000 - 143,000; Full time

Job summary

Bright Vision Technologies seeks a Machine Learning Infrastructure Engineer to design, build, and operate high-performance inference platforms for production ML workloads, focusing on latency, throughput, and observability.

This remote, full-time role requires 6+ years in distributed systems, strong Python and systems-language skills, and hands-on experience with LLM inference frameworks and GPU acceleration.

Qualifications

• Bachelor's or Master's in CS or related field.
• 6+ years in distributed systems, infrastructure, or ML platform engineering.
• Proficiency in Python and a systems language (Go, Rust, or C++).
• Experience operating high-throughput, low-latency services in production.
• Hands-on with LLM inference frameworks such as vLLM or TensorRT-LLM.
• Strong knowledge of GPU architecture and accelerator usage.
• Familiarity with Kubernetes, autoscaling, and cloud platforms.
• Experience with observability stacks (metrics, tracing, logging).
• Strong performance engineering and capacity planning.
• Excellent communication and incident response skills.

Responsibilities

• Design, build, and operate high-performance inference platforms for production ML workloads.
• Focus on systems engineering for AI deployment, including routing, batching, caching, and observability.
• Address latency, throughput, cost, and quality trade-offs in ML serving.

Skills

Distributed systems

Python

Go

Rust

C++

High-throughput systems

Observability

Kubernetes

Autoscaling

Performance engineering

Communication

Education

Bachelor's or Master's in CS

Tools

vLLM

TensorRT-LLM

Job description

Machine Learning Infrastructure Engineer – Remote

Job Title: Machine Learning Infrastructure Engineer
Location: 100% Remote (U.S.)
Position Type: Full-time, Direct W2
Salary Range: $105,000–$143,000 Annually
Experience Required: 6+ years

Sponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position.

Job Summary

We are seeking a Machine Learning Infrastructure Engineer to design, build, and operate high-performance, highly reliable inference platforms for serving large machine learning models in production. The role focuses on the systems engineering side of AI deployment, including request routing, batching, caching, autoscaling, GPU utilization, and end-to-end observability across diverse model workloads. The ideal candidate brings strong distributed systems and performance engineering expertise, has shipped serving systems at scale, and understands the trade-offs between latency, throughput, cost, and quality in ML serving.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science or a related field.
• Six or more years of experience in distributed systems, infrastructure, or ML platform engineering.
• Strong proficiency in Python and a systems language such as Go, Rust, or C++.
• Deep experience operating high-throughput, low-latency services in production.
• Hands-on experience with LLM or large model inference frameworks such as vLLM or TensorRT-LLM.
• Strong understanding of GPU architecture, memory hierarchies, and accelerator utilization.
• Familiarity with Kubernetes, autoscaling, and modern cloud platforms.
• Experience with observability stacks including metrics, tracing, and structured logging.
• Solid grounding in performance engineering and capacity planning.
• Strong communication and incident response skills.

Preferred Qualifications

• Open-source contributions to model serving infrastructure.
• Experience with multi-region or globally distributed AI serving.
• Familiarity with model quantization, distillation, and compression techniques.
• Exposure to FinOps for AI workloads and cost-efficient serving design.
• Experience supporting external-facing AI APIs at scale.

Equal Employment Opportunity (EEO) Statement

Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall.

BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees’ ability to perform their job duties may result in disciplinary action up to and including termination of employment.