Senior Machine Learning Engineer - Predictive Maintenance

About the Role
Our client, WhatJobs Direct, is actively seeking a Senior Machine Learning Engineer to spearhead our predictive maintenance initiatives. This is a fully remote position, allowing you to contribute your expertise from any location. You will be responsible for designing, developing, and deploying advanced machine learning models that predict equipment failures, optimize maintenance schedules, and minimize operational downtime. This role requires a deep understanding of statistical modeling, machine learning algorithms, data engineering, and cloud platforms. We are looking for a highly motivated individual with a proven track record in building and operationalizing ML solutions for industrial applications. Join our innovative, remote-first team and play a critical role in enhancing the reliability and efficiency of critical infrastructure. Your work will directly contribute to proactive problem-solving and operational excellence across various industries. This is an exciting opportunity to leverage data science for tangible operational improvements.Key Responsibilities
Design, develop, train, and deploy machine learning models for predictive maintenance, anomaly detection, and root cause analysis.Process and analyze large, complex datasets from various sources, including sensor data, maintenance logs, and operational parameters.Build data pipelines and feature engineering processes to prepare data for ML model training.Collaborate with domain experts, data engineers, and software developers to integrate ML solutions into existing systems.Evaluate model performance, conduct rigorous testing, and iterate on models to improve accuracy and reliability.Implement MLOps best practices for model deployment, monitoring, and management.Stay current with the latest research and advancements in machine learning and artificial intelligence.Mentor junior data scientists and ML engineers, fostering a culture of learning and innovation.Communicate complex findings and recommendations clearly to both technical and non-technical stakeholders.Contribute to the strategic direction of ML applications within the organization.Requirements
Master's or PhD degree in Computer Science, Data Science, Statistics, Engineering, or a related quantitative field.A minimum of 7 years of professional experience in machine learning engineering, with a focus on developing and deploying predictive models.Strong proficiency in programming languages such as Python (with libraries like scikit-learn, TensorFlow, PyTorch, Pandas, NumPy).Experience with cloud ML platforms (e.G., AWS SageMaker, Azure ML, Google AI Platform).Solid understanding of statistical modeling, time series analysis, and various ML algorithms (e.G., regression, classification, clustering, deep learning).Experience with data preprocessing, feature engineering, and model evaluation techniques.Familiarity with MLOps principles and tools.Excellent analytical, problem-solving, and critical thinking skills.Outstanding communication and collaboration abilities, essential for remote teamwork.Ability to work independently and manage projects effectively in a remote setting.Benefits
Fully remote work arrangement providing unparalleled flexibility and work-life balance.Highly competitive salary package with performance-based incentives.Comprehensive health, dental, and vision insurance plans.Generous retirement savings plan contributions.Significant paid time off and company holidays.Professional development budget for courses, certifications, and virtual conferences.Access to cutting-edge ML platforms and significant cloud computing resources.A collaborative and innovative remote-first company culture.Opportunities for significant career growth and impact.Support for home office setup and ongoing technical assistance.
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