COMPANY OVERVIEW

EchoTwin AI is pioneering AI-driven infrastructure intelligence, redefining how cities are managed. Powered by a proprietary visual intelligence engine with full spatial reasoning, EchoTwin transforms municipal fleets into mobile urban sensors—creating living digital twins that provide real-time insights into infrastructure, compliance, and safety. By enabling municipalities to proactively monitor, predict, and resolve issues, EchoTwin helps build resilient, self-healing, and sustainable urban ecosystems. More than “smart cities,” EchoTwin is advancing the era of cognizant cities—urban environments with the awareness to see, think, and act on challenges in real time.

QUALIFICATIONS

• Bachelor’s or Master’s degree in Mechanical Engineering, Electrical Engineering, Computer Science, Data Science, or a related field. A PhD is a plus.
• 3+ years of experience in prognostics, predictive maintenance, or reliability engineering, preferably in IoT or smart infrastructure environments.
• Proficiency in programming languages such as Python, R or Matlabfor data analysis, modeling, and algorithm development.
• Strong knowledge of machine learning techniques (e.g., regression, neural networks, time-series forecasting) and statistical methods for prognostics.
• Experience with data processing tools and frameworks (e.g., Pandas, NumPy, Scikit-learn, TensorFlow) and big data platforms (e.g., Hadoop, Spark).
• Familiarity with smart city technologies, including sensor networks, edge computing, and asset management software.
• Excellent problem-solving skills with the ability to handle complex, ambiguous data sets and derive actionable insights.
• Strong communication skills to convey technical concepts to non-technical stakeholders.
• Experience in urban asset monitoring, such as traffic systems, energy grids, or public safety infrastructure.
• Certification in relevant areas (e.g., Certified Reliability Engineer, Machine Learning Specialist).
• Knowledge of cloud platforms (e.g., AWS, Azure) for deploying scalable prognostic solutions.
• Prior work with simulation software (e.g., ANSYS, Simulink) for asset health modeling.

WHAT YOU’LL DO

The Prognostics Engineer will design, implement, and refine prognostic systems for monitoring smart city assets such as street signs, road conditions, transportation networks, utilities, and public facilities. You will use advanced analytics to predict potential failures, detect anomalies, and recommend proactive interventions, contributing to safer and more resilient cities.

KEY RESPONSIBILITIES

• Develop and deploy prognostic models and algorithms to forecast asset degradation, failures, and maintenance needs using data from edge computing devices, historical records, and real-time streams.
• Analyze large datasets from smart city assets to identify patterns, anomalies, and emerging issues, enabling early detection and resolution.
• Integrate prognostic tools with existing monitoring platforms, including issue tracking systems, to automate alerts, reporting, and decision-making processes.
• Collaborate with cross-functional teams (e.g., data scientists, software engineers, urban planners, and operations staff) to refine models based on feedback and real-world performance.
• Conduct simulations and validation tests to ensure the accuracy and reliability of prognostic predictions in diverse urban scenarios.
• Stay abreast of industry advancements in prognostics, machine learning, and smart city technologies, and recommend innovations to enhance system capabilities.
• Prepare technical documentation, reports, and presentations on prognostic findings, asset health metrics, and improvement strategies.
• Support compliance with regulatory standards for data privacy, safety, and environmental impact in smart city operations.