Machine Learning Engineer, Predictive Maintenance

AssetWatch serves global manufacturers by powering manufacturing uptime through the delivery of an unparalleled condition monitoring experience, with a passion to care about the assets our customers care for every day. We are a devoted and capable team that includes world-renowned engineers and distinguished business leaders united by a common goal – To build the future of predictive maintenance. As we enter the next phase of rapid growth, we are seeking people to help lead the journey. 

We are seeking a skilled Machine Learning Engineer with a strong background in signal processing and predictive maintenance. In this role, you will design, implement, and optimize models that leverage sensor data to detect anomalies, classify defects, predict equipment failures, and enhance overall reliability. You will work with cross-functional teams, including reliability engineers and MLOps, to deliver impactful solutions that keep critical systems running at peak efficiency.

This role is open to candidates based in the United States. We are currently unable to provide sponsorship of any kind. 

What You'll Do:

• Predictive Maintenance & Signal Processing
  • Perform robust data preprocessing, including filtering, cleaning, and transformation to ensure high-quality inputs for model development.
  • Employ frequency-domain and time-domain techniques to extract vital features from sensor signals.
  • Combine analytical techniques with in-depth expertise to transform raw sensor data into actionable insights, guiding maintenance decisions and enhancing machinery performance.
  • Explore novel algorithms to improve feature engineering and enhance model performance.
  • Work closely with condition monitoring engineers to refine predictive maintenance solutions
• Model Development & Deployment
  • Develop and refine machine learning models—ranging from classical algorithms to advanced deep learning approaches—to detect anomalies, diagnose issues, and predict failures.
  • Optimize model efficiency for real-world deployment, ensuring robust performance in operational environments.
  • Collaborate with MLOps and engineering teams to integrate models into production, ensuring scalability and reliability.
  • Continuously assess model performance, conduct experiments and iterative improvements to ensure models are robust and tailored to various industrial use cases.
  • Create dashboards and alerts that provide actionable intelligence to stakeholders.
• Collaboration & Knowledge Sharing
  • Communicate technical concepts and findings to diverse audiences, including operations, management, and technical peers.
  • Maintain thorough documentation of data processing pipelines, model architectures, and solution designs.
  • Contribute to an environment of continuous learning and best-practice sharing.

Who You Are:

• Educational Background
  • Master’s or Ph.D. in Mechanical Engineering, Electrical Engineering, Computer Science/Engineering, or a related field.
• Technical Expertise
  • Programming: Strong programming skills in Python (preferred), with proficiency in ML libraries like TensorFlow, or PyTorch.
  • Signal Processing: Solid grasp of time-series analysis and feature extraction methods (e.g., time domain analysis, spectral analysis, envelope analysis, wavelet analysis).
  • Machine Learning: Experience building models for anomaly detection, classification, or time-series forecasting.
  • Deployment & Data Management: Familiarity with cloud platforms (AWS, Azure), containerization (Docker), and SQL databases.
• Domain Knowledge
  • Proven experience in vibration analysis and fault detection of industrial systems and equipment (e.g., rotating machinery such as pumps, gearboxes, or electric motors).
• Soft Skills
  • Strong communication and presentation abilities, enabling effective collaboration across diverse teams.
  • Demonstrated problem-solving skills and proactive thinking in addressing complex industrial challenges.
  • A collaborative mindset with a willingness to share knowledge and support team members.

What We Offer: 

AssetWatch is a remote-first rapidly growing startup providing a game changing condition monitoring platform and mobile experience in the industrial manufacturing space. 

• Competitive compensation package including share options. 
• Flexible work schedule 
• Full benefits and 401K 
• Opportunity to make a real impact every day 
• Opportunity to work with an exciting and growing team 
• Unlimited PTO 

We have a distributed team that works remotely across locations in the United States. We are open to candidates from most states but collaboration within core working hours is required. 

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