Mechanical Engineering Specialist (Remote | $80-$130/hr)
3 days ago
City of London
Mechanical Engineering Expert \n \n Position: Mechanical Engineering Expert \n \n Type: Contractor \n \n Compensation: $80–$130/hour \n \n Location: Remote \n \n About the Opportunity \n micro1 is engaging highly skilled Mechanical Engineering Experts to contribute to an AI training project focused on engineering design, physical modeling, simulation, technical problem-solving, and Python-based engineering workflows. \n The work involves creating, solving, reviewing, and validating engineering tasks across structural, thermal, mechanical, and multiphysics domains. You may translate physical requirements into computational models, generate geometry or meshes, define materials and boundary conditions, run simulations, and determine whether engineering outputs satisfy applicable physical and design constraints. \n This role requires strong mechanical-engineering judgment and practical experience using engineering tools through code, scripts, configuration files, command-line interfaces, or programmatic APIs. Experience limited exclusively to graphical interfaces will not be sufficient. \n Responsibilities \n\n • Solve and validate mechanical-engineering problems involving design, analysis, simulation, testing, or R&D.\n, • Translate physical systems and engineering requirements into analytical or computational models.\n, • Create or modify geometry, meshes, materials, loads, contacts, constraints, and solver inputs.\n, • Perform structural, thermal, dynamic, fatigue, buckling, vibration, or related engineering analyses.\n, • Use Python to automate model preparation, simulations, parameter sweeps, optimization, post-processing, and verification.\n, • Analyze stress, strain, displacement, temperature, heat flow, deformation, frequency response, safety factors, and other relevant outputs.\n, • Compare simulation results with hand calculations, experimental data, reference cases, or expected physical behavior.\n, • Diagnose invalid geometry, mesh issues, convergence failures, incorrect boundary conditions, and unrealistic outputs.\n, • Review AI-generated engineering solutions and identify reasoning errors, incorrect assumptions, and violations of physical constraints.\n, • Develop clear, reproducible reference solutions and objective validation checks.\n, • Iteratively improve designs for performance, mass, strength, stiffness, thermal behavior, reliability, or manufacturability.\n\n Required Qualifications \n\n • MS or PhD in Mechanical Engineering or a closely related engineering discipline; or\n, • BS in Mechanical Engineering plus at least 1–2 years of relevant professional experience in mechanical design, analysis, simulation, testing, or R&D.\n, • Strong understanding of applied mechanics and mechanical-engineering fundamentals.\n, • Experience developing analytical, computational, or simulation-based engineering solutions.\n, • Practical proficiency with Python.\n, • Experience with at least one mechanical-engineering, geometry, meshing, or simulation tool that can be operated through a CLI, scripting interface, configuration files, or programmatic API.\n, • Ability to select and justify loads, boundary conditions, material properties, physical assumptions, and model fidelity.\n, • Ability to troubleshoot simulations and determine whether results are physically reasonable.\n, • Ability to clearly explain engineering decisions, limitations, and technical trade-offs.\n\n Preferred Qualifications \n\n • Experience with programmatic engineering tools such as CalculiX, Gmsh, Elmer, FEniCSx, CadQuery, OpenSCAD, OpenFOAM, or equivalent software.\n, • Experience with Python libraries and tools such as NumPy, SciPy, SymPy, pandas, Matplotlib, Jupyter, CAD or meshing APIs, finite-element libraries, optimization packages, or domain-specific scientific tools.\n, • Experience working across multiple engineering domains, including structural, thermal, dynamic, fatigue, buckling, vibration, or multiphysics analysis.\n, • Experience with engineering design optimization, simulation validation, or computational R&D.\n, • Ability to develop reproducible computational workflows and objective engineering validation methods.\n, • Experience reviewing technical or AI-generated engineering solutions for accuracy and physical validity.\n\n Key Areas of Expertise \n\n • Mechanical Engineering\n, • Engineering Design & Analysis\n, • Computational Modeling\n, • Simulation & Validation\n, • Structural Analysis\n, • Thermal Analysis\n, • Multiphysics Engineering\n, • Finite Element Analysis\n, • CAD & Geometry Generation\n, • Meshing\n, • Python-Based Engineering Automation\n, • Engineering Optimization\n, • Physical Modeling\n, • Failure & Convergence Diagnosis\n\n Compensation \n\n • $80–$130 per hour\n, • Contractor engagement\n, • Approximately 15 hours per week\n, • Fully remote and globally available\n, • Flexible schedule—you choose the hours and days you work, including weekends if desired\n, • Compensation is output-based, with experts paid per task that meets project specifications.\n, • Minimum submission requirements apply, and task completion time may vary depending on experience and workflow.\n\n Eligibility \n\n • Candidates must have relevant academic and/or professional experience in mechanical engineering or a closely related discipline.\n, • Strong mechanical-engineering fundamentals and computational/simulation experience are required.\n, • Practical Python proficiency is required.\n, • Experience with at least one programmatic or CLI-accessible engineering tool is required.\n, • Candidates must be able to assess whether engineering results are physically reasonable.\n, • Candidates should be available for approximately 15 hours per week with a flexible schedule.\n, • Selected experts should be prepared to begin promptly following onboarding.\n\n Application Process \n\n • Submit your application and complete the screening questions.\n, • Complete an AI interview of approximately 30 minutes.\n, • Complete a technical assessment, if required.\n, • Complete the hiring manager review.\n, • If selected, complete onboarding and begin the first task within 24–48 hours.\n\n
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