The Applied Machine Learning group is responsible for innovation and development of end-to-end AI solutions, technology proof of concepts, and IP development of current and future ML workloads for Intel architecture and silicon serving consumer and corporate business requirements. In this position, you will be responsible for research, modeling, prototyping, productizing of ML techniques, generating data insights and optimizations for Intel platforms. Responsibilities include but are not limited to: Builds machine learning based products/solutions, which provide descriptive, diagnostic, predictive, or prescriptive models based on data.Uses or develops machine learning algorithms, such as supervised and unsupervised learning, deep learning, reinforcement learning, generative AI, large language model and others, to solve applied problems in various disciplines such as Data Analytics, Computer Vision, Natural Language Processing, Recommendation System, Graph Neural Network, Robotics, etc. Interacts with users to define requirements for breakthrough product/solutions. In either research environments or specific product environments, utilizes current programming methodologies to translate machine learning models and data processing methods into software. Completes programming, testing, debugging, documentation and/or deployment of the solution/products. Engineers big data computing frameworks, data modeling and other relevant software tools.You will play a key technical role for end-2-end machine learning and deep learning platform development based on various frameworks and hardware (such as CPU, GPU, accelerators). You will also be responsible for developing AI ML solutions and methodologies to bring the best performance, accuracy, efficiency, and ease-of-use to customers by working with internal and external partners. The job scope may include but not limited to: End-2-end ML and DL platform component innovation and feature development in data ingestion, feature engineering, distributed training via data and model parallelization, hyper-parameter optimization, neural architecture search, model compression, quantization, distillation, and model serving; Algorithm and model development of advanced technologies in computer vision, natural language processing, large language model, recommendation, graph analytics, reinforcement learning, and other domains; Machine learning framework and workload performance profiling, optimization, insights generation for benchmark such as MLPerf as well as real-world customer use cases; Software and tools development in python, C++, and other languages as required. Top candidates will exhibit the following behavioral traits: Excellent written and oral communication skills. Be able to clearly communicate technical details and concept.
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Job Type
Full-time
Career Level
Mid Level
Number of Employees
5,001-10,000 employees