Senior Computing & IT Domain Expert (AI Training, Benchmarking & Technical Evaluation)

Innodata Inc.; Philippines; Remote; PHP 1,000,000 - 1,800,000; Full time

Benefits offered by this job

Flexible remote-friendly work环境

Opportunity to shape AI future

Competitive compensation

Job summary

Innodata Inc. seeks a Senior Computing & IT Domain Expert to bridge advanced CS systems and AI. You will evaluate complex visuals, design AI assessment benchmarks, validate model outputs, and ensure the accuracy of computing intelligence.

You will apply expertise in performance engineering, networking, digital hardware design, distributed systems, and HPC to drive rigorous evaluations and high-quality AI solutions across teams.

Qualifications

• Education in CS/CE/EE or related field.
• 3+ years in performance engineering, distributed systems, or HPC.
• Hands-on with flame graphs, trace waterfalls, and roofline plots.
• Experience with AI model evaluation or data annotation is a plus.
• Excellent technical writing and communication skills.

Responsibilities

• Interpret, analyze, and validate complex diagrams, charts, and topology maps.
• Profile and optimize performance using flame graphs and telemetry.
• Design, evaluate, and troubleshoot network topology and routing.
• Interpret digital design and timing diagrams for synchronous hardware verification.
• Analyze distributed systems observability via trace waterfalls and latency measurements.
• Evaluate HPC performance with roofline plots and memory intensity.

Skills

Analytical thinking

Problem solving

Technical communication

Research skills

Digital literacy

Teamwork

Attention to detail

Education

CS/CE/EE degree

Tools

Flame graphs

Trace waterfalls

Roofline plots

AI evaluation frameworks

Performance profiling tools

Job description

We are seeking a specialized Senior Computing & IT Domain Expert to bridge the gap between advanced computer science systems and artificial intelligence. In this role, you will leverage your deep technical background in performance engineering, networking, digital hardware design, distributed systems, and High-Performance Computing (HPC) to evaluate complex technical visuals, design rigorous AI assessment benchmarks, validate model outputs, and ensure the absolute accuracy and reliability of computing intelligence.

Core Responsibilities & Competencies

Interpret, analyze, and validate complex technical diagrams, system charts, performance graphs, architecture schematics, and network topology maps. Your specialized subject-matter expertise will cover:

• Performance Profiling & Optimization: Analysis of performance bottlenecks utilizing flame graphs and system telemetry.
• Networking & Infrastructure: Design, evaluation, and troubleshooting of network topology and routing protocols.
• Hardware & Digital Design: Interpretation of digital design and timing diagrams for synchronous systems and hardware verification.
• Distributed Systems: Analysis of distributed-systems observability utilizing trace waterfalls and request latencies.
• High-Performance Computing (HPC): Evaluation of compute and memory intensity via HPC performance analysis and roofline plots.

2. Analytical Thinking & Problem Solving

• Apply critical thinking, rigorous evidence evaluation, and independent problem-solving to complex, unstructured computing and IT architecture challenges.
• Validate technical solutions, system configurations, and algorithmic efficiencies against established industry standards and computational limits.

3. Problem Design & Technical Communication

• Develop challenging, high-fidelity tasks, technical questions, problem templates, and gold-standard reference solutions for AI training and evaluation.
• Document and explain complex computing architectures, debugging workflows, and performance tuning methodologies clearly for cross-functional teams.

4. Evaluation, Quality & Fairness

• Conduct meticulous technical reviews, error detection, and accuracy validations on technical datasets, code snippets, and AI model outputs.
• Calibrate quality standards and design fair, robust assessments that accurately measure genuine advanced computing and IT expertise.

5. Research, Digital Literacy & Professional Practice

• Perform comprehensive technical research, source validation, licensing verification, and data provenance checks.
• Utilize modern digital tools and participate actively in AI/LLM evaluation workflows (e.g., RLHF, domain benchmarking, and model alignment for code and systems).
• Maintain meticulous attention to detail, collaborate effectively with diverse teams, and adapt rapidly to evolving project needs.

Qualifications & Requirements

• Education: Bachelor’s, Master’s, or Ph.D. degree in Computer Science, Computer Engineering, Software Engineering, Electrical Engineering, or a closely related technical discipline.
• Experience: 3+ years of professional or advanced research experience in performance engineering, distributed systems, systems architecture, or HPC environments.
• Technical Proficiency:
• Hands-on experience reading and analyzing performance profiles (flame graphs, trace waterfalls, roofline plots) and timing/network schematics.
• Familiarity with AI model evaluation, data annotation, or prompt engineering frameworks is a strong plus.
• Communication: Exceptional technical writing, documentation, and communication skills.

What We Offer

• Competitive compensation package.
• Flexible remote-friendly work environment.
• Unique opportunity to shape the future of artificial intelligence by embedding expert-level computing and systems knowledge into advanced language and vision models.