Job Description

Classification: Non-Exempt Grade: E2 Reports To: Project Manager or Team Lead Working Hours: 8 to 12 hour shifts in a 24 X 7 schedule Summary: As an RF Data Collection Technician I, you will learn to collect cellular network baseline data and file reports back to company HQ. Drive Testers use vehicles in the performance of their duties and use test equipment to collect sensitive cellular network data. RF Data Collection Technician I will work in varying locations and perform various aspects of the job. This job is a good fit for people who: Are seeking an entry level position with opportunity for career growth. Are interested in electronics, radio signal theory and cellular communications. Have a good understanding of computers and software such as MS Outlook, Word and Excel, GPS navigation, file transfer protocol, and technical cellular phone applications. Can quickly master new business and technology software programs. Have no travel, driving or workday restrictions and can drive at night for an extended time. Can safely multi-task in a vehicle. Are very flexible in work hours and locations. Essential Functions: Learn all aspects of the job quickly and work independently with little supervision Collect propagation and signal measurement data for the analysis of RF performance Measure field data for the base station to identify RF signals frequencies and respective power levels Follow test plans, follow test site scheduling, understand equipment calibration and setup, RF signal measurement and basic data analysis. Work independently days or nights to gather relevant RF data, as required by the project Other Functions: Independently plan routes and manage time required to execute the amount of work that is planned for the project timeline (day/week) Quickly learn and retain relevant system knowledge through applied learning, reading of standards documents or other documentation and review of test plan documents Resolve basic computer problems with navigation and data collection software Demonstrate basic understanding of RF theory Extended hours in a vehicle Work on day shift or night shift as needed Overnight hotel stays as needed, on occasion Requirements: Must be 21 or older Must be based in or near the specified work location Excellent driving record - with at least 2 years driving experience in the US College desired, high school Graduate required Must be willing to learn the TEMS, XCAL or other comprehensive RF data collection tools Must have basic Microsoft Word, Excel and Outlook skills Flexible to travel and work aggressive schedules including night shift Must be able to pass standard background check including driving record Good written and verbal English language communication skills Location: Hybrid (Philadelphia, PA or Washington, DC) ***Must be US citizen or Green Card Holder. Job Summary: We are seeking a skilled and experienced Machine Learning (Client) Engineer to join our team in a customer-facing role. You will architect and implement innovative Client solutions, working closely with data scientists and engineers to put algorithms and models into practice to solve our customers' most challenging problems. You will take the lead in planning, designing, and running experiments, while researching new algorithms to deliver impactful solutions. Key Responsibilities: Design, build, and deploy machine learning models within the proposed platform, ensuring they are optimized for performance and scalability. Collaborate with Data Scientists and Data Engineers to implement feature stores, model management (MLOps), and Explainable AI (XAI) capabilities. Monitor and optimize the performance of deployed models, ensuring they meet business requirements and performance standards. Support model management, versioning, and deployment workflows to streamline the operationalization of machine learning models. Engage directly with customers to understand their business problems and help implement tailored Client solutions. Deliver Machine Learning projects end-to-end, including understanding business needs, planning projects, aggregating & exploring data, building & validating predictive models, and deploying completed Client capabilities on the AWS Cloud to deliver business impact. Utilize deep learning frameworks like PyTorch and TensorFlow to build computer vision models for versatile applications. Work on large-scale datasets, creating scalable, robust, and accurate computer vision systems. Collaborate with Cloud Architects to build secure, robust, and easy-to-deploy cloud-native machine learning solutions. Work closely with customer account teams and product engineering teams to optimize model implementations and deploy cutting-edge algorithms. Assist customers with Machine Learning Operations (MLOps) workflows such as model deployment, retraining, testing, and performance monitoring. Apply best practices from core Software Development activities to Machine Learning, including deplorability, unit testing, and structured, extensible software development. Preferred Qualifications: Proven experience in building and deploying machine learning models at scale. Proficiency with deep learning frameworks like PyTorch and TensorFlow. Experience with cloud-native machine learning solutions, preferably on AWS. Experience with Databricks Experience with Agile Methodology Strong understanding of MLOps workflows, including model management. Ability to work independently and collaboratively with cross-functional teams. #J-18808-Ljbffr Glow Networks, Inc.

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