CyberCoders
Title:
AI Systems Engineer
Location:
FULLY remote!
Salary:
$175k-$250k base + RSUs + Full Benefits
Requirements:
3+ years of Systems Engineering/DevOps/AI Infrastructure, AI, Python/Golang/Rust, and HPC experience
Our HPC infrastructure goes beyond just the GPU - allowing companies to train, iterate, and deploy AI & ML projects faster than ever! We specialize in high-performance GPU cloud solutions tailored for AI & ML projects and cutting-edge infrastructure (including GPU clusters, high-speed networking, and scalable storage) to support demanding workloads. Our services are designed to optimize performance, reliability, and affordability for AI researchers, ML engineers, and enterprises.
We're currently experiencing MASSIVE GROWTH... Our revenue grew over 95% in the last YEAR! We have made several acquisitions and formed several partnerships during this period of growth, and we need YOUR HELP to keep it going...
We're currently seeking a talented and highly motivated AI Systems Engineer to design, build, and optimize the infrastructure that powers AI-driven applications. You'll work at the intersection of hardware, software, and data - enabling efficient deployment of AI models and solutions at scale.
The ideal candidates have a strong background in systems engineering, high-performance computing, software defined networking, and general software development, with some experience in machine learning and deploying/maintaining AI systems in production.
What You'll Be Doing
AI Infrastructure Design and Development:
Design and implement scalable AI/ML infrastructure.
Optimize AI pipelines for performance and reliability.
Integrate AI models using CI/CD best practices.
Model Deployment and Optimization:
Deploy AI models in various environments (cloud, edge, on-premises).
Optimize inference performance for latency, throughput, and energy efficiency.
Use tools like TensorRT and ONNX to accelerate models.
Maintain HPC clusters, GPUs, and distributed systems.
Develop tools for system monitoring and troubleshooting.
Ensure AI system reliability through proactive maintenance.
Collaboration and Cross-Functional Work:
Align AI systems with overall product architecture.
Support AI researchers with efficient data pipelines and computing environments.
Security and Compliance:
Ensure compliance with security standards and data privacy regulations.
Secure sensitive data and models in production.
Stay updated with AI and machine learning advancements.
Integrate new tools and methods to enhance systems.
What You Need for this Position
5+ years of
Systems Engineering, DevOps, or AI/ML Infrastructure
experience
2+ years of experience in
High Performance Computing
Experience building cloud computing platforms (from scratch is a huge plus)
Hands‑on experience with
AI frameworks
(TensorFlow, PyTorch, etc.)
Experience deploying AI/ML models in production environments
#J-18808-Ljbffr
AI Systems Engineer
Location:
FULLY remote!
Salary:
$175k-$250k base + RSUs + Full Benefits
Requirements:
3+ years of Systems Engineering/DevOps/AI Infrastructure, AI, Python/Golang/Rust, and HPC experience
Our HPC infrastructure goes beyond just the GPU - allowing companies to train, iterate, and deploy AI & ML projects faster than ever! We specialize in high-performance GPU cloud solutions tailored for AI & ML projects and cutting-edge infrastructure (including GPU clusters, high-speed networking, and scalable storage) to support demanding workloads. Our services are designed to optimize performance, reliability, and affordability for AI researchers, ML engineers, and enterprises.
We're currently experiencing MASSIVE GROWTH... Our revenue grew over 95% in the last YEAR! We have made several acquisitions and formed several partnerships during this period of growth, and we need YOUR HELP to keep it going...
We're currently seeking a talented and highly motivated AI Systems Engineer to design, build, and optimize the infrastructure that powers AI-driven applications. You'll work at the intersection of hardware, software, and data - enabling efficient deployment of AI models and solutions at scale.
The ideal candidates have a strong background in systems engineering, high-performance computing, software defined networking, and general software development, with some experience in machine learning and deploying/maintaining AI systems in production.
What You'll Be Doing
AI Infrastructure Design and Development:
Design and implement scalable AI/ML infrastructure.
Optimize AI pipelines for performance and reliability.
Integrate AI models using CI/CD best practices.
Model Deployment and Optimization:
Deploy AI models in various environments (cloud, edge, on-premises).
Optimize inference performance for latency, throughput, and energy efficiency.
Use tools like TensorRT and ONNX to accelerate models.
Maintain HPC clusters, GPUs, and distributed systems.
Develop tools for system monitoring and troubleshooting.
Ensure AI system reliability through proactive maintenance.
Collaboration and Cross-Functional Work:
Align AI systems with overall product architecture.
Support AI researchers with efficient data pipelines and computing environments.
Security and Compliance:
Ensure compliance with security standards and data privacy regulations.
Secure sensitive data and models in production.
Stay updated with AI and machine learning advancements.
Integrate new tools and methods to enhance systems.
What You Need for this Position
5+ years of
Systems Engineering, DevOps, or AI/ML Infrastructure
experience
2+ years of experience in
High Performance Computing
Experience building cloud computing platforms (from scratch is a huge plus)
Hands‑on experience with
AI frameworks
(TensorFlow, PyTorch, etc.)
Experience deploying AI/ML models in production environments
#J-18808-Ljbffr