DeWinter Group

PHM Monitor Development Contractor

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a PHM Monitor Development Contractor in Foster City, CA, for 6+ months at $60-$65/hr. Requires 3+ years in PHM, a relevant BS degree, expertise in PySpark, Python, and Databricks, and strong communication skills.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
520
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🗓️ - Date
June 27, 2026
🕒 - Duration
More than 6 months
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🏝️ - Location
On-site
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📄 - Contract
W2 Contractor
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🔒 - Security
Unknown
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📍 - Location detailed
Foster City, CA
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🧠 - Skills detailed
#Batch #PySpark #Deployment #PyTorch #Data Manipulation #Python #Documentation #Signal Processing #Forecasting #Databricks #TensorFlow #Data Engineering #Anomaly Detection #"ETL (Extract #Transform #Load)" #Airflow #Data Science #ML (Machine Learning) #Monitoring #Spark (Apache Spark)
Role description
Title: PHM Monitor Development Contractor Job Type: Contract (W2 Only) Contract Length: 6+ months Pay Range: $60 - $65/hr Start Date: ASAP Location: Foster City, CA About The Opportunity Our client, a leader in autonomous vehicle technology, is looking for a skilled PHM Monitor Development Contractor to join their team for a 6+ month engagement. This project involves designing, developing, and deploying offline health monitoring algorithms and prognostic models for a fleet of autonomous vehicles. This is a high-impact role that requires a self-motivated professional who can hit the ground running to help predict component failures, estimate Remaining Useful Life (RUL), and optimize preventative maintenance schedules. Key Responsibilities & Deliverables This role is focused on the successful completion of specific tasks and deliverables. Your responsibilities will include: • Model Design: Designing and training data-driven and physics-based prognostic models to detect faults and estimate the Remaining Useful Life (RUL) of critical hardware components. • Algorithm Development: Developing offline diagnostic algorithms to detect anomalies, wear-and-tear patterns, and early fault indicators using batch telemetry, sensor logs, and historical maintenance data. • Data Engineering: Performing large-scale ETL and data manipulation using PySpark on Databricks clusters, and engineering, packaging, and deploying models using production-grade pipelines. • Validation & Testing: Rigorously back-testing prognostic models against historical failure data to ensure high accuracy, low false-positive rates, and reliability. • Deployment & Reporting: Designing fleet result dashboards, developing robust alerting strategies, and providing clear technical documentation of model architectures and deployment procedures. Required Skills & Experience: We are looking for someone with a proven track record of successful contract engagements. The ideal candidate will have: • 3+ years of experience specifically focused on Prognostics and Health Management (PHM), predictive maintenance, or reliability engineering. • A BS degree in Mechanical Engineering, Electrical Engineering, Data Science, or a related field. • Expertise in PySpark and Python for large-scale data manipulation, ETL, and feature engineering. • Hands-on experience working with the Databricks platform for development and deployment, and scheduling analytical workflows using Airflow DAGs. • Proficiency in anomaly detection, time-series forecasting, survival analysis, and ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch). • Familiarity with applying signal processing techniques (e.g., FFT, wavelet transforms) and understanding hardware mechanics/failure modes (FMEA/FMECA). • Demonstrated ability to work autonomously and manage your own time effectively to meet project goals. • Strong communication skills to provide clear technical documentation and status updates. • W2 only (No C2C or 1099 contractors)