AI Optimization Engineer

About This Opportunity

We are representing a confidential technology consulting organization seeking an AI Optimization Engineer for a 100% remote position within the United States. This is a direct-hire, full-time W2 role requiring 6+ years of experience in performance engineering, ML systems, or high-performance computing.

Our client is an established firm delivering cloud, AI, and enterprise solutions. This role offers tremendous career growth potential for the right candidate who can demonstrate measurable impact on production AI workloads.

Responsibilities

In this role, you will focus on extracting maximum throughput, minimizing latency, and reducing costs across training and inference workloads for large neural network systems. Your work will span the full stack from low-level kernel optimization to distributed system tuning.

• Optimize deep learning workloads on modern GPUs with a focus on production environments
• Apply distributed training and inference techniques to improve system performance
• Instrument and measure AI systems to enable rigorous, data-driven optimization decisions
• Collaborate with cross-functional partners including product, design, engineering, operations, and business stakeholders
• Translate ambiguous requirements into well-engineered solutions
• Participate in code review, design review, and mentorship of junior engineers
• Manage GPU architecture, model parallelism, memory management, and compiler-level optimization
• Implement model compression techniques while maintaining accuracy standards

What We're Looking For

Required qualifications:

• Bachelor's or Master's degree in Computer Science, Computer Engineering, or related field
• 6+ years of experience in performance engineering, ML systems, or HPC
• Strong proficiency in Python and C++
• Hands-on experience optimizing deep learning workloads on modern GPUs
• Deep understanding of distributed training and inference techniques
• Experience with profiling tools across CPU, GPU, and distributed systems
• Familiarity with model compression techniques and their accuracy implications
• Strong grasp of memory hierarchies, communication primitives, and parallelism strategies
• Excellent measurement, debugging, and analytical reasoning skills
• Strong communication and collaboration abilities

Preferred qualifications:

• Experience optimizing LLM inference at production scale
• Contributions to vLLM, TensorRT-LLM, DeepSpeed, or similar open-source projects
• Familiarity with custom kernel authoring in Triton or CUTLASS
• Experience with FinOps for AI workloads
• Publications or conference talks on AI systems performance

Visa sponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. New H-1B visa sponsorship is not available for this position.

How We Work With You

When you apply through Get A Job.ai, our talent team will review your qualifications and conduct an initial screening. If there's a strong match, we will submit your profile to our client for consideration. Please do not contact the client directly—all communication should go through our recruiting team to ensure the best outcome for your candidacy.

Pay

Pay via Get A Job.ai: $100,000 annually.

Equal Employment Opportunity: Get A Job.ai is committed to equal employment opportunity for all applicants regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic under applicable law.