مهندس موقع (مدني)

Company Description ARKAN for Construction is a specialized firm focused on high-quality interior finishing for residential and commercial projects. The company is committed to delivering precise, durable, and aesthetically refined finishes that align with client requirements and industry standards. ARKAN emphasizes collaboration, professionalism, and attention to detail across all project phases. Team members have the opportunity to work on diverse projects, contribute to visible outcomes, and develop their technical expertise in interior finishing engineering. Role Description The Finishing Engineer is a full-time, on-site role based in El Sherouk. The role involves supervising and executing interior finishing works, including coordination with site engineers, contractors, and suppliers to ensure materials and workmanship meet approved designs and specifications. The Finishing Engineer will review drawings, prepare work schedules, monitor progress, and ensure compliance with quality, safety, and time standards. Daily tasks include inspecting ongoing work, resolving technical issues, documenting site activities, and reporting project status to management. The role also requires collaboration with cross-functional teams to optimize finishing solutions and maintain clear communication with stakeholders. Qualifications Strong knowledge of interior finishing works (e.g., flooring, painting, ceilings, woodwork, tiling) and related construction techniques. Ability to read and interpret architectural and interior design drawings, details, and specifications. Experience in site supervision, quality control, and coordination with contractors and subcontractors. Proficiency in using construction-related software and tools (e.g., AutoCAD, MS Office, project scheduling tools) is preferred. Bachelor’s degree in Civil Engineering, Architecture, or a related field. Strong organizational, problem-solving, and time-management skills with attention to detail. Effective communication skills and ability to work collaboratively on-site in El Sherouk. Previous experience in interior finishing for residential or commercial projects is an advantage. Show more

About Turing: Turing is one of the world’s fastest-growing AI companies, accelerating the advancement and deployment of powerful AI systems. Turing helps customers in two ways: Working with the world’s leading AI labs to advance frontier model capabilities in thinking, reasoning, coding, agentic behavior, multimodality, multilinguality, STEM and frontier knowledge; and leveraging that work to build real-world AI systems that solve mission-critical priorities for companies. Role Overview: We are seeking an experienced Civil or Structural Engineering expert to lead a pod of trainers building realistic, terminal-based technical tasks for Terminal Bench Science. You will review every task your trainers produce for engineering correctness, reproducibility, and grader reliability, and coach trainers to consistently deliver high-quality tasks. Reporting Structure: Reports to the Civil & Structural Engineering Team Lead. Leads a pod of approximately 5–10 trainers. What you'll do: Review engineering tasks end to end, including problem statements, structural and geotechnical models, load cases, simulation data, computational environments, reference solutions, and automated tests. Validate tasks involving structural analysis, finite-element methods (FEA), earthquake and wind engineering, structural dynamics, geotechnical modeling, hydraulics, hydrology, transportation, and infrastructure systems. Ensure tasks require genuine multi-step engineering reasoning and reflect realistic civil and structural engineering workflows. Verify engineering accuracy across units, equilibrium, boundary conditions, load combinations, design codes, numerical stability, convergence, and safety factors. Validate computational models, solvers, dependencies, and simulation results for reproducibility and technical correctness. Review automated graders to ensure they evaluate meaningful engineering outputs such as forces, deflections, drifts, settlements, factors of safety, flow rates, and structural performance. Identify technical errors, unrealistic assumptions, incorrect tolerances, and opportunities to bypass engineering analysis. Provide clear, actionable feedback to task developers and track revisions through completion. Mentor and support technical trainers, allocate work, monitor quality and productivity, and resolve technical blockers. Maintain quality standards, technical documentation, and best practices across engineering task development. What we're looking for: Ph.D., postdoctoral experience, or equivalent advanced technical experience in Civil Engineering, Structural Engineering, Geotechnical Engineering, or a closely related discipline. Strong programming experience in Python, C/C++, Julia, Fortran, or MATLAB/Octave, with proficiency in Linux environments. Hands-on expertise in at least one major area: structural analysis, FEA, earthquake engineering, geotechnical modeling, or hydraulic/hydrological modeling. Strong understanding of engineering principles, numerical methods, simulation workflows, and model validation. Working knowledge of engineering design standards such as ASCE 7, ACI, AISC, Eurocodes, or IS codes. Experience reviewing complex technical work, engineering simulations, research outputs, or computational models. Strong analytical judgment with the ability to identify technical inaccuracies, edge cases, and flawed engineering assumptions. Experience mentoring, reviewing, or leading small technical teams. Excellent written communication skills for providing precise technical feedback and documenting quality standards. Nice to have: Experience with engineering simulation and analysis tools such as OpenSees/OpenSeesPy, Code_Aster, CalculiX, FEniCS, Gmsh, PyNite, EPANET, SWMM, HEC-RAS, MODFLOW, SUMO, QGIS, or GDAL. Familiarity with commercial engineering software such as SAP2000, ETABS, Abaqus, PLAXIS, or STAAD.Pro. Experience with nonlinear time-history analysis, performance-based design, reliability analysis, or structural health monitoring. Familiarity with Docker, Git, CI/CD pipelines, and automated testing. Experience developing or evaluating AI coding agents, terminal-based agents, or LLM-generated engineering solutions. Professional engineering licensure such as PE, SE, CEng, or equivalent. Industry experience working on buildings, bridges, transportation networks, water systems, or major infrastructure projects. Prior experience in AI training, technical quality control, benchmark development, or evaluation programs. Offer Details: Commitments Required: At least 4 hours per day and minimum 40 hours per week with overlap of 4 hours with PST. Employment type : Contractor assignment (no medical/paid leave) Duration of contract : 4 week [expected start date is next week] Show more

About Turing: Turing is one of the world’s fastest-growing AI companies, accelerating the advancement and deployment of powerful AI systems. Turing helps customers in two ways: Working with the world’s leading AI labs to advance frontier model capabilities in thinking, reasoning, coding, agentic behavior, multimodality, multilinguality, STEM and frontier knowledge; and leveraging that work to build real-world AI systems that solve mission-critical priorities for companies. Role Overview: We are seeking an experienced Mechanical or Aerospace Engineering expert to lead a team of technical trainers developing realistic, terminal-based engineering tasks for a frontier AI training and evaluation initiative. In this role, you will oversee a pod of approximately 5–10 trainers, review engineering tasks for technical accuracy, reproducibility, and evaluation quality, and ensure that tasks reflect authentic mechanical and aerospace engineering workflows. You will also mentor trainers, maintain quality standards, and drive consistent task delivery. What you'll do: Lead and mentor a pod of technical trainers, ensuring consistent quality, productivity, and timely delivery of engineering tasks. Review engineering tasks end to end, including problem statements, geometry and mesh files, simulation inputs, material properties, reference solutions, and automated tests. Validate tasks involving finite-element analysis (FEA), computational fluid dynamics (CFD), thermodynamics, heat transfer, dynamics, robotics, flight simulation, propulsion, and orbital mechanics. Ensure tasks reflect realistic mechanical and aerospace engineering workflows and require meaningful multi-step technical reasoning. Verify engineering correctness across units, equilibrium, conservation laws, boundary conditions, mesh convergence, solver tolerances, reference frames, and numerical stability. Validate computational environments, simulation tools, solvers, and dependencies to ensure reproducible results. Review automated graders to ensure they evaluate meaningful engineering outputs such as stresses, deflections, natural frequencies, aerodynamic coefficients, thermal performance, orbital parameters, and safety margins. Identify technical inaccuracies, unrealistic assumptions, incorrect tolerances, and opportunities to bypass engineering calculations or simulations. Provide clear, actionable technical feedback, track revisions, and ensure quality issues are resolved before task approval. Onboard trainers, allocate work, monitor quality and throughput, escalate blockers, and maintain technical documentation and best practices. What we're looking for: Ph.D., postdoctoral experience, or equivalent advanced technical experience in Mechanical Engineering, Aerospace Engineering, or a closely related discipline. Strong programming skills in Python, C/C++, Fortran, Julia, or MATLAB/Octave, with proficiency in Linux environments. Hands-on expertise in at least one major area: FEA, CFD, dynamics, flight simulation, thermal modeling, astrodynamics, guidance, navigation and control (GNC), or propulsion modeling. Strong understanding of engineering simulation, numerical methods, computational modeling, and technical validation. Experience reviewing complex technical work, engineering simulations, computational models, or research outputs. Ability to evaluate engineering assumptions, numerical accuracy, solver convergence, and the reliability of computational results. Strong analytical judgment with the ability to identify technical errors, edge cases, and flawed engineering assumptions. Experience mentoring, reviewing, or leading small technical teams. Excellent written communication skills for providing precise technical feedback and documenting quality standards. Nice to have: Experience with engineering simulation and computational tools such as OpenFOAM, SU2, CalculiX, Code_Aster, FEniCS, Elmer, Gmsh, FreeCAD, CadQuery, MuJoCo, ROS, XFOIL, AVL, OpenVSP, JSBSim, OpenMDAO, pyCycle, poliastro, Orekit, GMAT, or SPICE. Familiarity with commercial engineering software such as ANSYS, Abaqus, COMSOL, or NASTRAN, including reproducing workflows using open-source tools. Experience with state estimation, trajectory optimization, topology optimization, aeroelastic analysis, or multidisciplinary design optimization. Familiarity with Docker, Git, CI/CD pipelines, and automated testing. Experience developing or evaluating AI coding agents, terminal-based agents, or LLM-generated engineering solutions. Industry or agency experience in automotive, energy, manufacturing, robotics, aircraft, launch vehicles, satellites, or UAVs. Prior experience in AI training, technical quality control, benchmark development, or evaluation programs. Offer Details: Commitments Required: At least 4 hours per day and minimum 40 hours per week with overlap of 4 hours with PST. Employment type : Contractor assignment (no medical/paid leave) Duration of contract : 4 week [expected start date is next week] Show more

About Turing: Turing is one of the world’s fastest-growing AI companies, accelerating the advancement and deployment of powerful AI systems. Turing helps customers in two ways: Working with the world’s leading AI labs to advance frontier model capabilities in thinking, reasoning, coding, agentic behavior, multimodality, multilinguality, STEM and frontier knowledge; and leveraging that work to build real-world AI systems that solve mission-critical priorities for companies. Role Overview: We are seeking an experienced Chemical Engineering expert to lead a team of technical trainers developing realistic, terminal-based engineering tasks for a frontier AI training and evaluation initiative. In this role, you will oversee a pod of approximately 5–10 trainers, review chemical engineering tasks for technical accuracy, reproducibility, and evaluation quality, and ensure tasks reflect authentic chemical engineering workflows. You will also mentor trainers, maintain quality standards, and drive consistent task delivery. What you'll do: Lead and mentor a pod of technical trainers, ensuring consistent quality, productivity, and timely delivery of chemical engineering tasks. Review engineering tasks end to end, including problem statements, reaction kinetics, thermodynamic and property data, process flowsheets, computational environments, reference solutions, and automated tests. Validate tasks involving reaction engineering, thermodynamics, phase equilibria, transport phenomena, separation processes, process simulation, process control, optimization, combustion, and electrochemical engineering. Ensure tasks reflect realistic chemical engineering workflows and require meaningful multi-step technical reasoning. Verify engineering correctness across mass and energy balances, thermodynamic consistency, property data, unit handling, and numerical convergence. Validate computational models, stiff ODE/DAE solvers, solver tolerances, initial conditions, and simulation results to ensure reproducibility and technical accuracy. Review automated graders to ensure they evaluate meaningful engineering outputs such as conversion, yield, selectivity, purity, energy consumption, and process constraint satisfaction. Identify technical inaccuracies, unrealistic assumptions, incorrect tolerances, and opportunities to bypass engineering calculations or simulations. Provide clear, actionable technical feedback, track revisions, and ensure quality issues are resolved before task approval. Onboard trainers, allocate work, monitor quality and throughput, escalate blockers, and maintain technical documentation and best practices. What we're looking for: Ph.D., postdoctoral experience, or equivalent advanced technical experience in Chemical Engineering. Strong programming skills in Python, Julia, C/C++, or MATLAB/Octave, with proficiency in Linux environments. Hands-on expertise in at least one major area: process modeling, reaction kinetics, thermodynamic modeling, process simulation, or optimization. Strong understanding of chemical engineering fundamentals, numerical methods, computational modeling, and technical validation. Experience reviewing complex technical work, chemical process simulations, computational models, or research outputs. Ability to evaluate mass and energy balances, thermodynamic assumptions, numerical accuracy, solver convergence, and the reliability of computational results. Strong analytical judgment with the ability to identify technical errors, edge cases, and flawed engineering assumptions. Experience mentoring, reviewing, or leading small technical teams. Excellent written communication skills for providing precise technical feedback and documenting quality standards. Nice to have: Experience with chemical engineering simulation and computational tools such as Cantera, CoolProp, Pyomo, IDAES, DWSIM, CasADi, or OpenFOAM. Familiarity with commercial process simulation software such as Aspen Plus, Aspen HYSYS, or gPROMS, including reproducing workflows using open-source tools. Experience with process optimization, reactor modeling, separation systems, process control, or electrochemical simulations. Familiarity with Docker, Git, CI/CD pipelines, and automated testing. Experience developing or evaluating AI coding agents, terminal-based agents, or LLM-generated engineering solutions. Industry experience in petrochemicals, pharmaceuticals, energy, specialty chemicals, or chemical process manufacturing. Prior experience in AI training, technical quality control, benchmark development, or evaluation programs. Offer Details: Commitments Required: At least 4 hours per day and minimum 40 hours per week with overlap of 4 hours with PST. Employment type : Contractor assignment (no medical/paid leave) Duration of contract : 4 week [expected start date is next week] Show more