Tech companies have observed the importance of deep learning frameworks to gain different perspectives and drive better customer engagement in the global tech market. These tech companies are now opening multiple deep learning engineer jobs for aspiring as well as experienced deep learning engineers to work with machine learning and deep learning frameworks and tools. Deep learning vacancies are creating a storm in the market with technical details and knowledge of AI models with a lucrative salary package per annum offering. Deep learning engineer jobs are in high demand from students specializing in a Bachelor's or Master's degree in any technical field to work for tech companies and contribute to the tech society. Thus, let's explore some of the top ten deep learning engineer jobs in July 2022 to apply for.
Location: Santa Clara
Responsibilities: The deep learning engineer should be a part of a team of software engineers to develop algorithms for TensorFlow utilizing TensorRT. It is essential to implement new algorithms and integrate the latest TensorRT and CUDA features.
Qualifications: The candidate must have a Master's/Ph.D. in any technical field with more than five years of experience in software development. There should be sufficient knowledge of C++ programming and software design skills, machine learning algorithms, and frameworks.
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Location: Shanghai
Responsibilities: The deep learning engineer should invent and apply state-of-the-art deep learning algorithms to solve problems regarding autonomous vehicles, research object detection, and segment basis on types of data.
Qualifications: The candidate must have a Master's/Ph.D. in any technical field with more than three years of experience with sufficient knowledge of deep learning algorithms, computer vision, deep learning training framework, software design, and programming language.
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Location: Shanghai
Responsibilities: The deep learning engineer should build deep learning models for NLP for automotive applications, curate large problem-specific datasets, and drive an end-to-end workflow from data curation and training.
Qualifications: The candidate must have a B. Tech/M. Tech/Ph.D. in any quantitative field with over five years of experience in building deep learning models, frameworks, and programming language skills.
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Location: Seattle
Responsibilities: The deep learning engineer must help customers migrate their machine learning applications to Neuron and run high-performance search recommendations, computer vision, speech recognition, personalization, fraud detection, and natural language processing models with Inferentia. It is essential to develop integrations with The Neuron SDK and frameworks such as TensorFlow, PyTorch, and MXNet and plan while implementing new features, working with customers to create innovative solutions.
Qualifications: The candidate must have a B.S./Master's/Ph.D. in any technical field with more than five years of experience in software engineering, performance analysis, programming languages, and deep learning frameworks.
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Location: California
Responsibilities: The deep learning engineer should work on research and development of machine learning solutions for 3D gaming with the focus on advanced upscale techniques for providing better performance and quality boost on GPU.
Qualifications: The candidate must have a B.S/M.S./Ph.D. in any scientific field with more than four years, more than three years, and over one year of experience respectively. There should be sufficient knowledge of deep learning frameworks, 3D graphics, AI graphics techniques, ray tracing, and inference library applications for graphics.
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Location: Bangalore
Responsibilities: N/A
Qualifications: The candidate must have a Bachelor's degree in any technical field with four to seven years of experience in deep learning skills, programming and data structure, and image processing.
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Location: Bangalore
Responsibilities: The deep learning engineer needs to develop deep learning-based models and solutions to process, manage and interpret point cloud data from automated driving sensors (e.g RADAR and Lidar). These applications will help efficiently process a high volume of point cloud data from sensors (e.g. RADAR) and help improve perception in automated driving.
Qualifications: The candidate must have a Master's/Ph.D. in any technical field with sufficient knowledge in a programming language, deep learning frameworks, machine learning applications, MLOps tools, embedded systems, and many more.
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Location: Remote
Responsibilities: It is essential for deep learning engineer to build backend infrastructure, data pipelines, and/or deep learning models for AI-backed products, enhance existing deep learning systems using core coding skills while designing features, and builds large-scale recommendation systems.
Qualifications: The candidate must have a Bachelor's/Master's degree in any technical field with a minimum of three years of experience with proficiency in AI, deep learning, and machine learning technologies.
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Location: Bangalore
Responsibilities: The machine learning engineer is expected to participate and contribute to the creation of proofs of concept as part of pursuit or sales cycles, identify opportunities to apply the latest advancements in AI/ML to build, test, and validate predictive models, create algorithms and develop automated processes for predictive model validation, deployment, and implementation, and identify the data, technology and other requirements for implementing AI/ML models to solve problems.
Qualifications: The candidate must have a Bachelor's/Master's/ Advanced certifications in any technical field with more than three years of experience in machine learning technologies, programming languages, deep learning frameworks, model training, big data framework, and many more.
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Location: Bangalore
Responsibilities: The machine learning engineer needs to be responsible for the research and development of imaging, computer vision, and machine learning algorithms.
Qualifications: The candidate must have a Bachelor's degree in any technical field with more than two years of experience in applied mathematics, algorithm prototyping, programming language, ML lifecycle, data analysis tool, and state-of-the-art deep learning frameworks.
Click here to apply
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