Our company in the field of engineering, data intelligence, and AI-driven diagnostics, is seeking a highly skilled Mechanical / Signal Processing Engineer specializing in condition monitoring and profilometry analysis. The candidate will work on advanced sensor-based diagnostics, surface analysis, and fault detection in mechanical systems using signal processing, AI models and engineering-driven methodologies. If you are passionate about applying deep technical expertise to real-world industrial challenges and want to contribute to an international, engineering-focused environment, this role is ideal for you.
Responsibilities
Develop signal-processing algorithms for time-series and spatial profile data (FFT, filtering, spectral analysis, envelope detection, trend decomposition)
Build and validate alarm/threshold logic and event-detection rules for actionable maintenance triggers
Integrate multi-sensor inputs and fuse them into consolidated condition metrics
Evaluate ML or hybrid (rule , ML) approaches for anomaly detection and propose production steps
Validate sensor quality, calibration checks, and data lineage for each KPI
Support root-cause investigations, and help refine KPI definitions
Collaborate closely with the Machine Vision team: consuming their extracted variables and providing feedback to improve measurement quality and metadata
Identify and investigate data anomalies, inconsistencies, and quality issues
Prepare clear documentation, analytical reports, and summaries for internal teams
Requirements
Bachelor’s or higher in Mechanical Engineering, Electrical Engineering, Mechatronics, Signal Processing, or related fields
Strong background in mathematics & signal processing (time and frequency domain): filtering, FFT/PSD, envelope analysis, cross-correlation
Proficiency in Python and signal/array libraries (NumPy, SciPy)
Ability to recognize patterns, interpret sensor behavior, and extract meaningful insights
Strong documentation, organization, and task-tracking skills
Ability to work independently while collaborating effectively with technical teams
Professional English proficiency (upper-intermediate or higher), with the ability to read and fully comprehend technical documentation, research papers, and standards, and to prepare clear technical reports when required
Strong intellectual curiosity and proactive learning mindset, with the ability to rapidly adapt, independently acquire new domain knowledge, and integrate emerging technologies and AI advancements into diagnostic and signal-processing practices.
Preferred Qualifications (Nice-to-have)
Familiarity with fault diagnosis and fault detection
Experience with engineering or sensor datasets (acceleration, vibration, video profiling, etc.) and extracting diagnostic features from them
Understanding of signal-quality metrics, trend analysis, or event detection
Experience with accelerometer/vibration analysis and condition monitoring toolchains
Practical experience with profilometry, point-clouds, laser scanner data, or precision mechanical measurement workflows
Experience with MATLAB
Experience with AI & machine learning workflows
Basic experience with computer vision; (helpful for cross-team discussions, but not required)
Personal & Ethical Qualities
Teamwork spirit and cross-functional communication skills
Desire to grow, learn, and take ownership of tasks
Organization and responsibility in task execution with strong time-management and task prioritization skills
Systems thinking and the ability to understand complex, multi-component engineering workflows
Clear technical presentation and reporting capabilities
Analytical mindset and problem-solving attitude
Commitment, perseverance, and attention to detail
Creative thinker capable of generating value-added insights and new features from data
Working Conditions
position (Full-time (preferred) — Part-time negotiable based on alignment)
Working days: Sunday to Thursday
Working hours: Flexible schedule based on project needs
شرکت دانش بنیان پیشرو ابتکار و دانش، از واحدهای فناور مرکز رشد دانشگاه صنعتی شریف، پس از فعالیت در داخل کشور، در حال صادرات تجهیزات و محصولات خود در زمینه فناوری اطلاعات (iot) در صنعت ریلی به اتحادیه اروپا می باشد.