Technischer Koordinator unterstützt das Team bei der Organisation des Testlabors, Vorbereitung und Durchführung von Testaktivitäten und Koordination von Kalibrierungen, Wartungen und Reparaturen.
Compensation
Freiburg 39Std: €3.060 - €4.998 EUR Monthly
Responsibilities
Organisation und Verwaltung von Testequipment, Messmitteln, Testhardware und Testmaterialien
Vorbereitung und Nachbereitung von Testsystemen und Testaufbauten sowie Bereitstellung der erforderlichen Hardware
Unterstützung bei standardisierten Testaktivitäten, z. B. mechanischen Tests, Impact- und Drop-Tests, Reliability-Tests sowie automatisierten Testabläufen
Technische Dokumentation von Testaufbauten, Seriennummern, Prüfmitteln und Testergebnissen sowie strukturierte Archivierung relevanter Testdaten
Koordination von Kalibrierungen, Wartungen und Reparaturen von Test- und Laborequipment
Requirements
Abgeschlossene Berufsausbildung
Nice to have: Erfahrung mit Test-, Labor- oder Messequipment
Nice to have: Grundkenntnisse in technischen Testmethoden
Nice to have: Erfahrung mit Inventar- oder Verwaltungssystemen
Rivian is seeking an innovative engineer who combines expertise in AI/ML with a passion for quality and manufacturing excellence in the Body Assembly area. This role is crucial in driving our digital transformation initiatives through the development and implementation of AI-powered solutions.
Compensation
The salary range for this role is $98,500-$123,100 for Illinois based applicants.
Responsibilities
Apply fundamental process engineering principles and advanced statistical methods, including ML/AI algorithms, to analyze manufacturing data (e.g., End of line test data, sensor data, press data, LVDT data, historical trends, operational logs).
Develop and implement predictive models for key performance indicators (KPIs) such as yield, throughput and equipment downtime.
Collaborate with IT and operations teams to establish data pipelines, ensuring data quality, accessibility, and integrity for ML model training and deployment.
Utilize data collected by Rivian’s MES database system for model training.
Design, train, validate, and deploy robust ML models (e.g., classification, regression, time-series forecasting) for real-time process control, anomaly detection, predictive maintenance, and quality prediction.
Design, build, optimize, and maintain scalable data pipelines and analytical datasets supporting analytics, machine learning, and AI use cases.
Compensation
The anticipated compensation for this position is USD $123,650.00/Yr. - USD $203,150.00/Yr. depending on experience and qualifications.
Responsibilities
Design, build, optimize, and maintain scalable data pipelines and analytical datasets supporting analytics, machine learning, and AI use cases.
Build reliable data ingestion, transformation, and feature pipelines across large-scale product telemetry, customer, behavioral, feedback, and operational datasets.
Establish strong practices around data quality, observability, reliability, performance, and governance to ensure datasets are trusted and ready for analysis and modeling.
Use Python, SQL, Spark, and modern cloud data technologies to process, transform, analyze, and derive insights from large-scale datasets.
Analyze product telemetry, usage, behavioral, customer feedback, support, and operational datasets to identify trends, patterns, anomalies, friction points, and opportunities.
Requirements
Bachelor's or higher in Data Science, Machine Learning, Statistics, Applied Mathematics, Computer Science, or a related discipline
A Data/AI Developer focused on building and validating ML models for supply chain forecasting, developing LLM workflows, and managing MLOps on Databricks.
Compensation
The suggested pay for this position ranges from $95,546 to $105,875. The actual salary offer will carefully consider a wide range of factors, including your skills, qualifications, and location. Also, certain positions are eligible for additional forms of compensation, such as bonuses.
Responsibilities
Build and validate ML models for inventory and demand forecasting, and document model validation.
Automate identification and validation of product substitutions during supply disruptions.
Build LLM and agentic workflows inside a governed, auditable AI operating model.
Run MLOps on Databricks (MLflow, model serving, monitoring).
Deliver dashboards and analytics for supply chain stakeholders.
Requirements
Bachelor's degree in computer science, data science, statistics or a related field
Develop and deliver advanced digital solutions that support the design, construction, commissioning and operation of complex nuclear facilities, working at the intersection of engineering, software development, data analytics and advanced modeling.
Compensation
Expected compensation range is between $79,000-$132,000 annually depending on skills, experience, and geographical location.
Responsibilities
Design, develop and implement software applications and digital solutions to address complex engineering, project delivery and operational challenges.
Develop reusable digital tools and applications that improve efficiency, reduce risk and support informed decision-making.
Develop software using programming languages such as Python, C#, Java and SQL.
Design and implement data-driven applications that integrate information from multiple engineering, project and operational systems.
Develop prototypes and proof-of-concept solutions to demonstrate the potential value of new digital technologies.
Postdoctoral research fellow in the Department of Population Medicine at Harvard Pilgrim Health Care Institute and Harvard Medical School, focusing on statistical methods for genomics and omics data.
Compensation
$60,527.31 -$90,790.97
Responsibilities
Design research study and protocols, including creating detailed timelines, meeting with faculty and staff collaborators, planning for technical and data support, and creating survey instruments.
Prepare proposal for obtaining research funding & Sponsored Program Application including compiling documentary material for human studies review.
Provide day-to-day management for research projects, including overseeing the activities of research assistants, data collection, developing plans, conducting data analysis. Manage database design and development.
Prepare manuscripts detailing research findings and submit findings to peer-reviewed medical journals.
Perform out-of-the-box thinking, collaborate with others, and make a difference every day!
Requirements
Doctoral degree (PhD, ScD) in Biostatistics, Statistics, Bioinformatics, or related field
Design, develop, validate, and maintain workforce models and simulation capabilities to evaluate force structure changes, workforce flows, training pipelines, and readiness impacts, supporting workforce optimization and leadership decision-making.
Compensation
W2 Hourly rate: $45-$55. Pay rates are based on experience, qualifications, location, and certifications, and are subject to change at any time.
Responsibilities
Analyze, integrate, and prepare workforce, training, readiness, and force structure data from sources such as Envision, STARS DMOG, AFMA, ARM, LCOM, and AETC systems.
Develop and maintain workforce flow models, net flow analyses, and workforce health assessments to identify key drivers, bottlenecks, and constraints across the 2A force generation enterprise.
Design, develop, calibrate, and validate simulation models, including Discrete Event Simulation and System Dynamics, to evaluate workforce planning scenarios and force structure alternatives.
Apply quantitative analysis and forecasting techniques to assess workforce trends and readiness impacts.
Develop visualizations, dashboards, technical documentation, and analytical products to communicate findings and support leadership decision-making.
Requirements
Nice to have: Experience with Discrete Event Simulation modeling
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