Senior Machine Learning Engineer

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September 12

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Ampd Energy

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Energy • Construction • Hardware

Ampd Energy is a company dedicated to providing emission-free power solutions for industrial applications, particularly in environments where traditional diesel power is impractical or undesirable. They have developed the Ampd Enertainer, an advanced battery energy storage system aimed at replacing diesel generators on construction sites. The Enertainer significantly reduces harmful emissions and noise pollution and is easier, safer, and more cost-effective to operate. Ampd Energy's systems are connected and monitored remotely, ensuring reliability and efficiency. Their products are trusted by leading construction and real estate companies worldwide, aligning with the industry's shift toward electrification and sustainability.

51 - 200 employees

⚡ Energy

🔧 Hardware

💰 $8M Debt Financing on 2023-03

📋 Description

• 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.

🎯 Requirements

• 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

🏖️ Benefits

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