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FL
Fluence Labs
NDT Engineer (Entry Level)
Entry-Level JobVerifiedNo experience needed
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What they do
A Deep Learning Engineer designs, deploys, and optimizes deep learning models and algorithms. Responsibilities include training models using frameworks such as TensorFlow, PyTorch, and Keras, as well as evaluating models for accuracy. May work closely with data scientists, software engineers, and other stakeholders to develop solutions that meet business needs.
$148,278 / year median in Louisiana
Job Description
This role focuses on developing reconstruction and analysis algorithms for our advanced X-ray CT imaging systems. The position requires strong technical abilities in engineering and the capacity to collaborate effectively with both technical and non-technical team members. You will help ensure our imaging pipelines, data systems, and day-to-day technical operations run smoothly and reliably. Roles and Responsibilities Assist with the setup, calibration, and operation of NDT equipment Support certified technicians in performing inspections Help evaluate materials and components for defects or discontinuities according to established procedures Accurately document and record inspection results Maintain equipment and work areas to the highest standards of cleanliness and safety Participate in training programs and progressively take on more responsibility as skills develop Uphold Fluence Labs' commitment to safety, quality, and excellence on every job Process and analyze large-scale 3D volumetric datasets Prototype new algorithmic concepts and transition them into production software Design and execute simulation and experimental validation studies Collaborate closely with hardware, applications, and software engineering teams Required Qualifications Bachelor's degree (or equivalent relevant experience) in Computer Science, Electrical Engineering, Applied Mathematics, Imaging Science, Computational Physics, or a related field Familiarity with machine learning frameworks such as PyTorch or TensorFlow Some experience or coursework involving 3D or volumetric data processing • Basic understanding of inverse problems, numerical optimization, and signal/image processing concepts Preferred Skills Experience in computational physics or imaging system modeling Proven ability to transition research prototypes into production software Publication or patent record Exposure to high-performance computing environments Basic systems administration knowledge (server management, Microsoft 365, networking, scripting) Preferred Candidate Qualities Detail-oriented with strong foresight to anticipate and prevent issues Natural troubleshooting mindset for diagnosing and resolving complex technical problems Eagerness to learn new technologies and adapt rapidly in a dynamic environment Clear communicator capable of explaining technical concepts to diverse audiences