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Temporary Computer Vision Deep Learning Engineer Jobs in South Carolina

Learn and understand a large body of research in deep learning and machine learning * Participate in cutting-edge research for medical applications of computer vision Must Have Experience

Learn and understand a large body of research in deep learning and machine learning * Participate in cutting-edge research for medical applications of computer vision Must Have Experience

Learn and understand a large body of research in deep learning and machine learning * Participate in cutting-edge research for medical applications of computer vision Must Have Experience

Learn and understand a large body of research in deep learning and machine learning * Participate in cutting-edge research for medical applications of computer vision Must Have Experience

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Knowledge of deep learning frameworks and methodologies * Experience in applying machine learning ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Knowledge of deep learning frameworks and methodologies * Experience in applying machine learning ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Knowledge of deep learning frameworks and methodologies * Experience in applying machine learning ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Knowledge of deep learning frameworks and methodologies * Experience in applying machine learning ...

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Temporary Computer Vision Deep Learning Engineer information

What is the difference between Temporary Computer Vision Deep Learning Engineer vs Computer Vision Engineer?

AspectTemporary Computer Vision Deep Learning EngineerComputer Vision Engineer
CredentialsBachelor's or Master's in CS, AI, or related; experience with deep learning frameworksBachelor's or Master's in CS, AI, or related; experience with computer vision tools
Work EnvironmentProject-based, short-term contracts, often in tech or research firmsFull-time, ongoing roles in tech companies, startups, or research labs
Industry UsageCommon in consulting, research projects, or temporary assignmentsStandard role in product development, AI solutions, and software engineering

The main difference is that a Temporary Computer Vision Deep Learning Engineer works on short-term projects focusing on deep learning techniques for computer vision, while a Computer Vision Engineer typically holds a permanent position involved in ongoing development of computer vision applications. The temporary role emphasizes flexibility and project-specific skills, whereas the full-time role involves continuous integration into a company's long-term projects.

What are the most commonly searched types of Computer Vision Deep Learning Engineer jobs in South Carolina? The most popular types of Computer Vision Deep Learning Engineer jobs in South Carolina are:
What are popular job titles related to Temporary Computer Vision Deep Learning Engineer jobs in South Carolina? For Temporary Computer Vision Deep Learning Engineer jobs in South Carolina, the most frequently searched job titles are:
What job categories do people searching Temporary Computer Vision Deep Learning Engineer jobs in South Carolina look for? The top searched job categories for Temporary Computer Vision Deep Learning Engineer jobs in South Carolina are:
What cities in South Carolina are hiring for Temporary Computer Vision Deep Learning Engineer jobs? Cities in South Carolina with the most Temporary Computer Vision Deep Learning Engineer job openings:

Senior AI/ML C++ software engineer

Recruiting Engine (MLS)

Lexington, SC

$104K - $138K/yr

Full-time

Re-posted 9 days ago


Job description

Senior Embedded Controls Engineer: C++/Linux and Machine Learning exp.
As an AI Machine Learning Engineer focus will be on designing and developing scalable solutions using AI tools and machine learning models. Addressing various neural network-related challenges in transportation sector. This involves leveraging big data computation and storage tools to create prototypes and datasets, conducting model training and evaluations, integrating solutions, performing bench tests and onsite tests, tuning, and monitoring. Proficiency in languages such as C and C++ is required, along with software development for Linux platforms.
Your responsibilities
Design and develop real time AI ? Neural Network solutions for transportation industry maintenance equipment. Implementing appropriate ML algorithms.
Write clean, documented code following best practices.
Develop and implement communication protocols.
Work independently and collaboratively with a motivated team.
Generate requirements and design documentation.
Plan for, design, and deliver testing, and tested products into the QA process.
Apply communication and problem-solving skills to solve software issues related to the design, development, deployment, testing, and operation of systems.
Qualifications
Education
Master"s / Bachelor"s degree in Software Engineering or similar experience.
Experience
5+ years of experience in developing CNN, R-CNN type neural network for computer vision tasks.
5+ years of experience in Software development using C++ & Linux embedded.
Experience with Supervised and Semi-Supervised Learning, Deep Learning, Support Vector Machines, Linear and Logistic Regression.
Working knowledge of AI Framework such as TensorFlow, Caf?, PyTorch, Keras, Darknet and OpenCV.
Working knowledge of AI edge devices such as NVIDIA Jetson / Nano / Orin.
Knowledge of the Linux Operating System.
Preferred Experience
Experience using statistical computer languages (R, Python, SQL etc.) to manipulate data and draw insights from large data sets.
Experience working with and creating data architectures.
Knowledge of a variety of machine learning techniques (semantic segmentation, clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, and proper usage, etc.) and experience with applications.
Experience with edge computing & controlling devices (On-device deployment in C/C++ or similar) for real time application.
Experience with optimizing neural networks to perform well on low-power mobile platforms (e.g. pruning, distillation, quantization).