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Some experience understanding the AI/Client approachesMust understand the package management for various environments (Python, R, and Hadoop environments)Must have experience with administration of Hadoop ecosystem specifically HDFS, Hive, and SparkPython, OpenCV, Keras/PyTorch/Tensorflow Deep Learning/Machine Learning, Computer Vision (Image Classification, Object Detection.
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You will work with neural network frameworks like Pytorch and TensorFlow, extend our neural net engine to support the latest and SOTA DNNs emerging from the research community and industry, and optimize for Qualcomm next generation hardware acceleration cores (Hexagon DSP/Adreno GPU/CPU.
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Proficiency in Google Cloud Platform (GCP) services relevant to machine learning and AI, such as AI Platform, BigQuery, Dataflow, and Tensorflow. Experience with building and training machine learning models using tools like TensorFlow, Keras, or PyTorch.
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Utilize Spark, Databricks, Tensorflow, and Python to handle data extraction, analysis, and model development. Proficiency in Python development, Tensorflow, and Databricks. Utilize Spark, Databricks, Tensorflow, and Python to handle data extraction, analysis, and model development.
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Knowledge of frameworks and SDKs for Vision/Deep Learning (e.g. OpenCV, OpenCL, PyTorch, TensorFlow etc. This role will play a central role in the evolution of automotive cockpit, ADAS/autonomous driving and high-performance compute platforms.
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Experience in Object Oriented Programming (Java, Scala, Python), SQL, Unix scripting or related programming languages and exposure to some of Python’s ML ecosystem (numpy, panda, sklearn, tensorflow, etc.
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Experience with deep learning frameworks such as Pytorch, Jax, or Tensorflow. Experience applying artificial intelligence to a scientific domain such as computational photonics, computational design, computational chemistry, etc.
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Hybrid, 3 daysExperience with machine learning tools such as scikit-learn, R, Theano, TensorFlow, SparkML, or FoundryExperience in using two or more of the following modeling types to solve business problems: classification, regression, time series, clustering, text analytics, survival, association, optimization, reinforcement learning.
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Proficiency with deep learning frameworks like TensorFlow, PyTorch, and JAX. The company has raised $250 million from investors including Silver Lake, BOND, NEA, and Bob Iger. Initially, Genies were adopted by thousands of Hollywood icons including Justin Bieber and Rihanna through partnerships with Universal Music Group and Warner Music Group.
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Experience with deep learning frameworks such as Pytorch or Tensorflow. We are seeking individuals passionate in areas such as deep learning, computer vision, audio and speech processing, natural language processing, machine learning, reinforcement learning, computational statistics, and applied mathematics.
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Strong fluency in Python and SQL, experience with Tensorflow, PyTorch, Airflow and data warehouse. Experience with SQL and cloud technologies like Snowflake, Google BigQuery, Databricks, presto etc.
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Expert level of Advanced and Predictive Analytical Methods e.g., Simulation, Design of Experiments, Genetic Algorithms, Ensemble Methods, Naïve Bayes, Neural Networks, regression, image processing, natural language processing.
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Master one of several mainstream machine learning development framework such as PyTorch, TensorFlow, MXNet. You will work with a team of machine learning researchers to build AI software systems, learn about deep learning algorithms, and use your technical skills to advance autonomous driving.
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Bonus: Experience with deep learning frameworks, e.g., TensorFlow, PyTorch, etc., is a plus. Our researchers have a broad range of expertise related to computer science and electrical engineering, such as AI/ML, algorithms, digital signal processing, audio engineering, image processing, computer vision, data science & analytics, distributed systems, cloud, edge & mobile computing, computer networking, and IoT.
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Python, CUDA, TensorFlow, and PyTorch. We're currently looking for research engineers with specialized skills in LiDAR, camera, and radar perception technologies to enhance our autonomous driving systems' ability to understand and interact with complex environments.
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