Machine Learning Engineer (Predictive Maintenance)

- Experience building representative benchmark datasets, validating models against reviewed ground truth, analyzing false positives and false negatives, and creating repeatable evaluation or regression workflows is highly desirable - Hands-on experience architecting and delivering production ML solutions on AWS is required, including several of: SageMaker (Training, Processing, Pipelines, Model Registry, Endpoints), S3, Athena, AWS Glue, EMR, Lambda, Step Functions, ECS/Fargate, Timestream, Aurora/RDS, Amazon Bedrock, IoT Core, CloudWatch, and IAM - Physics-informed ML and experience with additional modalities (electrical/current signature analysis, ultrasound, oil analysis) are a plus - Experience designing data mining and annotation workflows in partnership with domain experts, including label taxonomy design, labeling tooling, label quality control, and converting noisy expert feedback into model-ready ground truth - Proficiency in scientific and ML/DL frameworks and libraries such as NumPy, Pandas, SciPy, scikit-learn, TensorFlow, PyTorch, or similar tools - Working knowledge of SQL (MySQL/Aurora, Athena) and the ability to independently explore, validate, and troubleshoot large and imperfect industrial datasets - Experience using Large Language Models, AI-assisted coding, and agentic AI tools for software and ML development; familiarity with designing or integrating LLM- or agent-based workflows for data processing, analysis, decision support, or automation is highly…