Remote | Hardware Expert (MSc. or PhD) — $60–$120/hour
About The Position
24-MAG LLC is recruiting experienced hardware engineering professionals for a remote freelance/contract consulting opportunity supporting advanced AI training and evaluation initiatives. Consultants will apply professional expertise to 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. Practical proficiency with coding agents is required. Assignments may cover hardware systems and architecture, engineering design, electronic systems, mechanical components, system integration, testing, validation, reliability, and failure analysis. Consultants will create rigorous, self-contained technical problems and reference solutions, assess AI-generated analyses and code, and provide detailed feedback. Work may use calculations, computational models, simulations, experimental reasoning, physical testing, test automation, and performance measurement. Deliverables should be technically accurate, reproducible, clearly documented, and consistent with real-world engineering constraints. This is a fully remote opportunity open worldwide, with an expected commitment of approximately 15 hours per week and a flexible schedule. Compensation is advertised at $60–$120 per hour, but payment is output-based and made per completed task meeting project specifications; task specifications and compensation depend on individual assignments. Selection may include screening questions, an approximately 30-minute AI interview, and hiring manager review. Selected professionals should be prepared to start their first assignment within 24–48 hours after onboarding. Work must not use confidential or proprietary information belonging to an employer, client, institution, or other third party.
Requirements
- 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.
- Demonstrated ownership of substantial engineering work involving hardware systems, products, technical research, or complex validation activities.
- Proficiency with relevant engineering software such as Python, MATLAB, Simulink, SPICE, Julia, C/C++, or comparable computational tools.
- Strong analytical reasoning, mathematical problem-solving, critical-thinking, and technical research capabilities.
- Ability to connect theoretical engineering principles with real-world design constraints, system behaviour, and practical implementation requirements.
- Ability to produce reproducible engineering calculations, simulation results, technical reports, or validation documentation.
- Exceptional attention to detail and commitment to accurate, independently verifiable work.
- Ability to clearly explain technical decisions, modelling assumptions, experimental findings, and engineering trade-offs.
- Strong independent working skills and ability to manage specialised technical assignments in a remote environment.
Nice To Haves
- Experience taking a hardware product or subsystem through development, testing, validation, or production.
- 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.
- Experience diagnosing complex engineering failures, evaluating technical discrepancies, and developing structured solutions.
- Experience designing test systems, validation procedures, reliability assessments, or automated engineering workflows.
- Prior experience with AI model training or evaluation projects.
Responsibilities
- Develop technically rigorous, self-contained hardware engineering problems based on realistic industry and research challenges.
- Analyse scenarios involving hardware design, electronic systems, mechanical components, integrated technologies, system requirements, operating conditions, performance constraints, and engineering specifications.
- Translate practical engineering requirements into technical questions, computational tasks, and evaluation criteria, applying first-principles reasoning to system behaviour and physical constraints.
- Evaluate hardware architectures, subsystem interactions, engineering design decisions, and component-to-system performance relationships.
- Develop reference solutions using engineering calculations, computational simulations, experimental reasoning, or other appropriate technical methods.
- Use relevant engineering tools to build and evaluate models, scripts, simulations, and computational solutions against requirements and physical constraints.
- Design or assess validation approaches involving physical testing, test automation, performance measurement, and technical verification.
- Use coding agents to support engineering analysis, computational problem-solving, simulation development, and technical workflows.
- Review and validate AI-generated engineering analyses, code, simulation outputs, and explanations; identify errors in assumptions, mathematical reasoning, implementations, and interpretation of results.
- Analyse reliability, system integration, testing, and failure-diagnosis scenarios; assess root-cause analysis, verification methodologies, and corrective engineering decisions.
- Produce technical documentation describing analytical methods, validation procedures, assumptions, and conclusions.
- Provide detailed technical feedback to improve AI performance in hardware engineering, analytical reasoning, and computational problem-solving.
- Ensure work is accurate, complete, reproducible, and consistent with real-world engineering constraints.
- Complete specialised assignments remotely, without using confidential or proprietary third-party information.
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What This Job Offers
Job Type
Part-time
Career Level
Mid Level
