Performance Engineer (C++, Python, Rust)

Accountabilities: The Performance Engineer will contribute technical expertise to AI training initiatives by designing challenging engineering tasks, evaluating solutions, and helping improve the quality of advanced AI systems. The role requires strong knowledge of systems optimization, programming languages, and performance engineering principles.

Collaborate with research and engineering teams to improve AI capabilities in systems programming, compiler optimization, runtime performance, and low-level engineering concepts.

Design realistic performance engineering challenges based on production-scale optimization scenarios.

Develop accurate, well-documented solutions to complex systems programming and optimization problems.

Review and assess AI-generated solutions, providing detailed feedback on correctness, efficiency, scalability, and engineering quality.

Build evaluation frameworks and scoring guidelines covering areas such as systems architecture, runtime optimization, compiler engineering, memory management, CPU/GPU performance, and concurrency.

Partner with other technical experts to maintain consistency, accuracy, and quality across AI training datasets.

Apply domain expertise to enhance the reasoning and problem-solving abilities of advanced AI models.

Identify opportunities to improve engineering workflows, benchmarks, and optimization methodologies.

Requirements:

The ideal candidate brings hands-on experience in performance engineering, systems programming, and software optimization, with the ability to communicate complex technical concepts clearly and effectively.

Minimum 2 years of professional experience in performance engineering, systems programming, or low-level software optimization.

Strong expertise in at least one of the following programming languages: C++, Python, or Rust, with familiarity across the others preferred.

Proven experience improving production systems through measurable performance gains, including latency reduction, throughput improvements, memory optimization, or runtime enhancements.

Strong understanding of systems architecture, compiler behavior, performance profiling, and optimization techniques.

Experience with benchmarking, profiling tools, and performance analysis methodologies.

Ability to analyze complex engineering problems and develop structured, high-quality solutions.

Excellent written communication skills with the ability to explain technical decisions and optimization strategies.

Demonstrated technical growth and increasing responsibility throughout a professional career.

Availability to commit approximately 40 hours per week during standard weekday business hours.

Preferred experience includes distributed systems, high-performance computing, compiler internals, operating systems, AI infrastructure, or collaboration with research teams.

Benefits:

Competitive compensation of $70–$110 per hour.

Fully remote work environment with flexible execution.

Opportunity to contribute to the development of advanced AI technologies.

Collaboration with experienced AI researchers and software engineering professionals.

Exposure to challenging, real-world systems optimization projects.

Meaningful technical work focused on improving next-generation AI capabilities.

Weekly payments processed through supported payment platforms.

Potential for project extensions based on business needs and performance.

How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!  Why Apply Through Jobgether? 

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