Senior ML Engineer, Multi-Sensor Modeling

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  "lists": [
    {
      "text": "Responsibilities ",
      "content": "<li>Develop algorithms that improve the speed, accuracy, and reliability of Gridware’s automated hazard detection systems</li><li>Work with multimodal time-series and spatial sensor data across diverse sampling rates and noise characteristics.</li><li>Design models that are robust, interpretable, and deployable in production environments.</li><li>Live in the data; help curate &amp; share strategic &amp; well-defined datasets that help solve our highest-value challenges</li><li>Explore advanced approaches such as graph-based learning for grid topology reasoning, geospatial modeling and localization and multimodal fusion across acoustic, magnetic, vibration, electrical, and visual signals</li><div><u>Production Engineering</u></div><li>Write clean, scalable, well-tested Python code that integrates into a large shared codebase.</li><li>Build end-to-end ML pipelines including data processing, feature extraction, training, evaluation, and deployment.</li><li>Optimize models for performance, reliability, and real-world constraints.</li><li>Collaborate on infrastructure for model monitoring, validation, and continuous improvement.</li><div><u>Collaboration &amp; Communication</u></div><li>Translate complex analyses into clear insights for engineers, operators, and leadership.</li><li>Frame solutions to ambiguous, open-ended problems to achieve buy-in from various stakeholders by focusing on the business impact of your projects</li><li>Communicate uncertainty, tradeoffs, and model behavior effectively.</li><li>Partner cross-functionally with software, data engineering, product, and event-reporting teams.</li><li>Help shape technical direction and best practices for ML at Gridware. This includes exemplifying standards for experiment tracking, model versioning, reproducibility, and lifecycle management.</li>"
    },
    {
      "text": "Required Skills",
      "content": "<li>5+ years of experience in machine learning, signal processing, or applied physics in production environments.</li><li>Strong programming skills in Python and experience contributing to large, shared codebases.</li><li>Experience working within modern software stacks, including cloud platforms, containerization, and CI/CD workflows</li><li>Excellent written and verbal communication, especially explaining data and models clearly.</li>"
    },
    {
      "text": "Bonus Skills",
      "content": "<li>Experience with Graph Neural Networks or learning over physical/topological systems.</li><li>Familiarity with power systems, embedded sensing, or edge ML.</li><li>Proven experience with time-series modeling and noisy real-world sensor data.</li><li>Experience with multimodal learning or sensor fusion.</li><li>Track record of technical leadership or mentoring.</li><div><br></div>"
    }
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    "team": "Automation",
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