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Ampd Energy

Senior Machine Learning Engineer

Fully Remote Engineering
Added
2 days ago
Location
Type
Full time
Salary
Not Specified

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Related skills

forecasting anomaly detection edge computing aws sagemaker real-time inference

About Ampd Energy

Ampd Energy is transforming how cities build - cleaner, smarter, and more sustainably. We are trailblazers in making the construction industry emission-free. Our flagship product, the Ampd Enertainer, is an advanced, compact, and connected battery energy storage system (BESS) designed to replace the dirty, noisy, and hazardous diesel generators that power construction sites around the world. By combining connected hardware with advanced software and AI, we reduce emissions, noise, and operational complexity.

We envision an emission-free future across all industries. Our mission is to develop robust, versatile, and easy-to-use products that deliver clean energy - empowering businesses and people to achieve more. We're seeking individuals who bring entrepreneurial drive, adaptability, and enthusiasm, and who thrive in an environment of continuous learning and evolution.

Overview

Join our mission to revolutionize renewable energy through cutting-edge Battery Energy Storage

Storage Systems (BESS). As a Senior Machine Learning Engineer, you’ll lead the

development of predictive maintenance models to enhance the reliability and efficiency

of our BESS solutions. You’ll be the go-to ML expert on our engineering team, driving

innovation by designing algorithms that predict component failures, optimize system

performance, and drive the deployment of them. Your work will directly impact the

scalability and sustainability of clean energy infrastructure worldwide and help ensure

our latest innovations usher us into the future.

Key Responsibilities

  • Develop and deploy predictive models for component failure and time-to-failure estimation using high-frequency sensor data.
  • Design advanced anomaly detection and time-series models to identify and mitigate risks in BESS operations.
  • Collaborate with data engineers to define and scale data pipelines for real-time and batch processing.
  • Partner with the platform team to deploy models on edge devices (e.g., IoT systems) and cloud-based inference systems.
  • Establish robust monitoring for model performance, including drift detection, degradation, and continuous improvement strategies.
  • Mentor junior software engineers and share expertise to elevate the team’s overall ML capabilities.

    • Required Experience

  • Proven expertise in applied ML engineering, with experience deploying customer-facing models to production. Typically 5+ years, but exceptions are made for significant experience demonstrations.
  • Hands-on experience with developing models for anomaly detection techniques (e.g., Isolation Forest, autoencoders, or one-class methods).
  • Strong proficiency in time-series modeling and predictive maintenance for industrial or physical systems.
  • Proficiency with AWS ML tools (e.g., SageMaker, IoT Core, Lambda) and real-time inference pipelines.
  • Ability to collaborate effectively with software and data engineers to build scalable ML infrastructure.
  • Strong problem-solving skills and a passion for tackling complex technical challenges.
  • Ability to understand the interconnectivity between business objectives and technical constraints, and make thoughtful recommendations on the best course of action

    • Preferred Experience

  • Knowledge of battery or energy storage systems and their degradation patterns (preferred but not required).
  • Experience deploying ML models on edge devices (e.g., AWS IoT Greengrass, Azure IoT Edge, or similar).
  • Familiarity with streaming data platforms (e.g., Kafka, Apache Spark Streaming, or equivalent).

    • What We Offer

  • Impactful Work: Contribute to the future of clean energy by improving the reliability of next-generation BESS technology.
  • Innovative Environment: Work with cutting-edge ML tools and collaborate with a passionate, cross-functional team.
  • Growth Opportunities: Access to professional development, mentorship, and opportunities to lead high-impact projects.
  • Flexible Culture: Enjoy a hybrid work model, competitive benefits, and a supportive team environment.

    • Additional Information

    Ampd Energy offers comprehensive benefits, professional development opportunities, and a multi-cultural, collaborative, and diverse environment.

    All information provided will be treated in strict confidence and used solely for recruitment purposes.

    Ampd Energy is an equal-opportunity employer. All candidates will be assessed on merit without regard to age, race, gender, sexual orientation, religion, nationality, marital status, political affiliation, or any other factor protected by law.

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