EchoTwin AI Logo

EchoTwin AI

Prognostics Engineer

Reposted 4 Days Ago
Be an Early Applicant
In-Office
San Francisco, CA, USA
Mid level
In-Office
San Francisco, CA, USA
Mid level
The Prognostics Engineer will develop models for predicting asset failures in smart cities using analytics, collaborating and validating findings with teams.
The summary above was generated by AI
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.

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.

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.

Benefits and Perks

There are endless learning and development opportunities from a highly diverse and talented peer group, including experts in various fields, including Computer Vision, GenAI, Digital Twin, Government Contracting, Systems and Device Engineering, Operations, Communications, and more!

  • Options for medical, dental, and vision coverage for employees and dependents (for US employees)

  • Flexible Spending Account (FSA) and Dependent Care Flexible Spending Account (DCFSA)

  • 401(k) with 3% company matching

  • Unlimited PTO

  • Profit sharing

Please do not forward resumes to our jobs alias, EchoTwin AI employees, or any other company location. EchoTwin AI is not responsible for any fees related to unsolicited resumes.

Life at EchoTwin AI

If you want to empower the world’s most important cities—and the institutions that run them—you belong here. At EchoTwin AI, we value excellence regardless of background and are committed to building a team that reflects the communities we serve.

EchoTwin AI is an Equal Opportunity Employer. We consider all qualified applicants without regard to race, color, religion, sex (including pregnancy), sexual orientation, gender identity or expression, national origin, age, disability, veteran status, genetic information, or any other status protected by applicable law.

EchoTwin AI San Francisco, California, USA Office

San Francisco, California, United States

Similar Jobs

9 Minutes Ago
Hybrid
Milpitas, CA, USA
Senior level
Senior level
Artificial Intelligence • Semiconductor
This role involves advanced troubleshooting, validation, and operational support for AI compute hardware, collaborating with engineering teams to ensure system performance.
Top Skills: BashPython
10 Minutes Ago
Remote or Hybrid
2 Locations
175K-195K Annually
Senior level
175K-195K Annually
Senior level
Artificial Intelligence • Security • Software • Analytics • Big Data Analytics
Design, build, and operate cloud-native, device-agnostic distributed systems using Go. Own architecture decisions, mentor engineers, promote testing and clean code, diagnose production issues, collaborate on roadmaps, and work with SRE to automate and improve reliability.
Top Skills: Cloud-NativeDistributed SystemsGoMicroservice ArchitectureTest Driven Development (Tdd)
24 Minutes Ago
In-Office
193K-241K Annually
Senior level
193K-241K Annually
Senior level
Software
Lead AI Observability product from vision through GA and post-GA growth. Own roadmap, business outcomes (adoption, retention, expansion), pricing, and exec reporting. Drive cross-functional engineering and design teams, partner with enterprise customers on production AI/LLM issues, build agentic AI prototypes, and iterate on features and packaging based on GA customer feedback.
Top Skills: Agentic Ai WorkflowsAi AgentsApmLlmsObservability

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account