Remote | Systems Performance Engineer — $65–$105/hour
24-Mag•New York, NY
•Remote
About The Position
We are seeking experienced US-based performance engineers for a specialized, full-time consulting opportunity. This role is crucial for a high-impact generative AI initiative, focusing on developing and evaluating advanced performance-engineering tasks for frontier model training and inference systems. Selected engineers will be responsible for designing technically challenging problems, producing rigorous solutions, assessing model-generated outputs, and establishing evaluation standards across key areas such as systems optimization, compiler engineering, runtime performance, latency, throughput, and memory efficiency.
Requirements
- At least 2 years of dedicated professional experience in performance engineering, systems programming, or low-level optimization.
- Deep hands-on expertise in C++, Python, or Rust.
- Working familiarity with the other listed languages is highly valuable.
- A measurable record of improving production-system latency, throughput, scalability, or memory efficiency.
- Strong knowledge of profiling, benchmarking, concurrency, memory management, and runtime behavior.
- Demonstrable professional growth and increasing technical responsibility.
- Strong written communication and the ability to explain complex technical decisions clearly.
- Reliable availability for a full-time, 40-hour weekday schedule.
- A degree in computer science, software engineering, computer engineering, applied mathematics, or a related technical field is highly relevant.
- Equivalent professional experience in production systems or performance optimization may also be considered.
- Advanced work involving operating systems, runtime development, compiler technology, or large-scale infrastructure is especially valuable.
Nice To Haves
- Experience optimizing AI training, inference, or high-performance computing workloads.
- Familiarity with compiler internals, intermediate representations, code generation, or runtime systems.
- Knowledge of CPU and GPU architecture, cache behavior, vectorization, and parallel execution.
- Experience using profilers, tracing systems, benchmarking frameworks, and performance-analysis tools.
- Familiarity with distributed systems, multithreading, asynchronous execution, or memory allocators.
- Previous involvement in technical review, engineering mentorship, or rubric development.
- Experience collaborating with research scientists, infrastructure teams, or compiler engineers.
- Graduate-level education in systems engineering, compilers, distributed computing, or high-performance computing may be helpful.
Responsibilities
- Analyze performance across production systems, AI workloads, runtime environments, and supporting infrastructure.
- Identify bottlenecks affecting latency, throughput, memory consumption, and computational efficiency.
- Evaluate systems-level optimization strategies across C++, Python, and Rust applications.
- Guide research and engineering teams on runtime behavior, resource utilization, and performance trade-offs.
- Design challenging performance-engineering tasks grounded in realistic systems and infrastructure scenarios.
- Write accurate, technically rigorous, and well-structured solutions.
- Develop problems involving profiling, benchmarking, concurrency, memory management, runtime efficiency, and systems architecture.
- Ensure tasks reflect practical performance challenges found in production AI and software environments.
- Review technical solutions written in C++, Python, Rust, or related systems languages.
- Assess implementation correctness, computational complexity, memory behavior, and execution efficiency.
- Evaluate concurrency models, data structures, compiler behavior, and runtime design decisions.
- Identify optimization opportunities while considering maintainability, reliability, and system-level trade-offs.
- Compare alternative technical solutions and determine which approach is more accurate and effective.
- Provide clear written feedback on performance, correctness, systems design, and optimization quality.
- Develop detailed rubrics for evaluating performance-engineering tasks across AI workloads.
- Collaborate with other technical specialists to maintain consistency and accuracy across training data.
Benefits
- Competitive hourly compensation ($65–$105/hour)
- Full-time W-2 contingent employment arrangement
- Fully remote role
- Opportunity to contribute to advanced generative AI initiatives
- Work on challenging systems programming and performance optimization problems
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What This Job Offers
Job Type
Full-time
Career Level
Senior
