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Open nowFirst seen 31 hours ago

Remote | Hardware Expert (MSc. or PhD) — $60–$120/hour

24-MAG343 open roles

Where
New York, United States, Remote
Work mode
Remote
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Your applicationOpen nowRemote | Hardware Expert (MSc. or PhD) — $60–$120/hour24-MAG · New York, United States, Remote

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The clock on this job

Early applications get read.

12.1% of postings close within 7 days. Measured by our own scanner across the market. 24-MAG postings stay open a median of 1 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: first seen 31 hours ago

24-MAG median: 1 days open

The posting

We are sharing a specialised remote consulting opportunity for experienced Hardware Engineering Professionals with strong expertise in hardware systems, engineering design, simulation, technical validation, reliability analysis, and AI-assisted coding workflows to contribute their professional knowledge to advanced AI training and evaluation initiatives.

Selected professionals will develop, solve, review, and validate challenging hardware engineering problems based on realistic industrial and research scenarios. The work combines first-principles engineering reasoning with computational modelling, quantitative analysis, simulation, experimental validation, and coding-agent-assisted workflows to help improve the accuracy, technical reasoning, and reliability of advanced AI systems. Practical experience using coding agents is required.

Key Responsibilities

Hardware Engineering & Technical Problem Development

  • Develop technically rigorous, self-contained hardware engineering problems reflecting realistic industry and research challenges
  • Analyse complex engineering scenarios involving hardware design, electronic systems, mechanical components, and integrated technologies
  • Translate practical engineering requirements into clearly defined technical questions, computational tasks, and evaluation criteria
  • Apply first-principles reasoning to evaluate system behaviour, physical constraints, and engineering design considerations
  • Contribute specialised technical expertise to the development of challenging AI training and evaluation assignments

Hardware Systems Design & Engineering Analysis

  • Evaluate hardware architectures, subsystem interactions, and engineering design decisions across relevant technical domains
  • Analyse system requirements, operating conditions, performance constraints, and relevant engineering specifications
  • Apply knowledge of hardware design, RTL-related concepts where relevant, and systems engineering principles to complex technical scenarios
  • Examine relationships between component-level behaviour, system integration, and overall hardware performance
  • Develop structured engineering analyses explaining design assumptions, technical trade-offs, and practical implementation considerations

Simulation, Testing & Technical Validation

  • Develop reference solutions using engineering calculations, computational simulations, experimental reasoning, or appropriate technical methods
  • Apply relevant engineering tools such as Python, MATLAB, Simulink, SPICE, Julia, C/C++, or comparable software
  • Evaluate simulation results and technical models against applicable engineering requirements and physical constraints
  • Design or assess validation approaches involving physical testing, test automation, performance measurement, and technical verification
  • Identify discrepancies between expected and observed system behaviour and explain their engineering implications

Coding Agents & AI Engineering Evaluation

  • Use coding agents to support engineering analysis, computational problem-solving, simulation development, and technical workflow execution
  • Develop reproducible scripts, computational models, and reference solutions for complex hardware-related tasks
  • Review and validate AI-generated engineering analyses, code, simulation outputs, and technical explanations
  • Identify errors in engineering assumptions, mathematical reasoning, computational implementations, and result interpretation
  • Provide detailed technical feedback to improve AI performance across hardware engineering, analytical reasoning, and computational problem-solving

Hardware Reliability & Engineering Quality Assurance

  • Analyse engineering scenarios involving hardware reliability, system integration, testing, and failure diagnosis
  • Evaluate root-cause analysis approaches, verification methodologies, and corrective engineering decisions
  • Review technical solutions for accuracy, completeness, reproducibility, and consistency with real-world engineering constraints
  • Produce clear technical documentation explaining analytical methods, validation procedures, assumptions, and engineering conclusions
  • Apply rigorous quality standards to hardware research, simulation-based analysis, and specialised AI evaluation deliverables

Ideal Profile

  • Bachelor's, Master's, or PhD degree in Electrical Engineering, Mechanical Engineering, Mechatronics, Aerospace Engineering, Systems Engineering, Applied Physics, or a closely related discipline
  • Significant professional or research experience in hardware engineering, product development, systems integration, testing, validation, reliability, or failure analysis
  • Strong understanding of engineering fundamentals, physical systems, quantitative analysis, and technical problem-solving
  • Practical experience using coding agents in engineering or technical workflows is required
  • Demonstrated ownership of substantial engineering work involving hardware systems, products, technical research, or complex validation activities
  • Experience taking a hardware product or subsystem through development, testing, validation, or production is highly relevant
  • Practical knowledge of engineering simulation, computational modelling, experimental analysis, or technical verification methodologies
  • Experience developing or validating engineering models against physical measurements or experimental data
  • Familiarity with hardware design, electronic systems, RTL-related workflows, or multidisciplinary systems engineering is advantageous
  • Demonstrated ability to diagnose complex engineering failures, evaluate technical discrepancies, and develop structured solutions
  • Experience designing test systems, validation procedures, reliability assessments, or automated engineering workflows
  • Proficiency with relevant engineering software such as Python, MATLAB, Simulink, SPICE, Julia, C/C++, or comparable computational tools
  • Ability to connect theoretical engineering principles with real-world design constraints, system behaviour, and practical implementation requirements
  • Strong analytical reasoning, mathematical problem-solving, critical-thinking, and technical research capabilities
  • Experience producing reproducible engineering calculations, simulation results, technical reports, or validation documentation
  • Exceptional attention to detail and commitment to accurate, independently verifiable engineering work
  • Ability to explain technical decisions, modelling assumptions, experimental findings, and engineering trade-offs clearly
  • Strong independent working skills and the ability to manage specialised technical assignments within a remote environment
  • Prior experience with AI model training or evaluation projects is advantageous but not required

Engagement Details

  • Freelance / contract engagement
  • Fully remote — open worldwide
  • Compensation: $60–$120/hour advertised rate range
  • Payment Structure: Output-based compensation, with payment made per completed task that meets project specifications
  • Expected Commitment: Approximately 15 hours per week
  • Flexible Schedule: Professionals may choose their preferred working hours and days, including weekends
  • 10 available openings
  • Specialised engineering consulting role spanning hardware systems, technical simulation, engineering validation, reliability analysis, and AI training
  • Technical Requirement: Practical proficiency with coding agents is required
  • Work will involve engineering problem development, computational analysis, simulation, reference solution creation, and AI-generated technical content evaluation
  • Assignments will draw on practical expertise in hardware engineering, systems integration, testing, validation, and failure analysis
  • Task specifications, submission requirements, and compensation will depend on individual assignments
  • Selection may include screening questions, an approximately 30-minute AI interview, and a hiring manager review
  • Selected professionals should be prepared to begin their first assignment within 24–48 hours of completing onboarding
  • Work must be completed without using confidential or proprietary information belonging to any employer, client, institution, or other third party

About the Platform

This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.

By submitting this application, you acknowledge that your information may be processed by 24-MAG LLC for recruitment and opportunity matching in accordance with our Privacy Policy: https://www.24-mag.com/privacy-policy

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