AI Optimization Engineer

Location: 100% remote within the United States

Salary: $100,000 annually

Company

Technology consulting and software development organization delivering cloud, AI, data, and enterprise solutions across the United States.

What you will do

• Optimize training and inference workloads for large neural network systems to increase throughput, reduce latency, and control costs.
• Improve performance across the stack, from low-level kernels and compiler optimizations to distributed system configuration.
• Analyze GPU architecture, model parallelism, memory management, communication primitives, and parallel execution strategies.
• Profile and measure CPU, GPU, and distributed workloads to guide data-driven optimization decisions.
• Collaborate with product, design, engineering, operations, and business stakeholders to turn ambiguous requirements into production-ready solutions.
• Contribute through code reviews, design reviews, mentoring, and delivery of reliable production systems.

Requirements

• Must be eligible to work in the United States as a U.S. citizen, Green Card holder, EAD holder, or H-1B transfer candidate.
• New H-1B visa petitions cannot be sponsored for this position.
• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related field.
• 6+ years of experience in performance engineering, ML systems, or high-performance computing.
• Strong proficiency in Python and C++, with hands-on experience optimizing deep learning workloads on modern GPUs.
• Experience with distributed training and inference, profiling tools, model compression, debugging, measurement, and analytical reasoning.

Nice to have

• Production-scale LLM inference optimization experience.
• Contributions to vLLM, TensorRT-LLM, DeepSpeed, or similar projects.
• Experience authoring custom kernels with Triton or CUTLASS.
• Experience with FinOps for AI workloads.
• Publications or talks on AI systems performance.

Culture & Benefits

• Fully remote work within the United States.
• Full-time direct W-2 employment.
• Career growth opportunities within an established organization.
• Cross-functional collaboration with product, design, engineering, operations, and business stakeholders.
• Equal employment opportunity and a workplace free from discrimination and harassment.