Machine Learning Software Engineer

Santa Clara, CA 95050
  • Job Code
Job Description

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, and prototyping 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, Bayesian analysis and others, to solve applied problems in various disciplines such as Data Analytics, Computer Vision, 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 & 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/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, recommendation, 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.

An ideal candidate would exhibit behavioral skills that indicate:

  • Excellent written and oral communication skills and be able to clearly communicate technical details and concept.


You must possess the below minimum qualifications to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates. Experience listed below would be obtained through a combination of your school-work/classes/research and/or relevant previous job and/or internship experiences.

Minimum Qualifications:
Master's with 3+ years or Ph.D. with 2+ years  in Computer Engineering or
 Computer Science or  Software Engineering or Electrical Engineering or Physics or Mathematics or Aerospace engineering or applied mathematics or related technical discipline.

3+years of the following technical skills:

  • Experience in deep learning frameworks such as PyTorch or TensorFlow or MXNet working on CPU / GPU / AI accelerators for ML/DL
  • Strong experience with Performance optimization / tuning
  • Familiar with deep learning algorithm as well as traditional data analyze algorithm such as SVM or  PCA or K-mean, XGBoost, etc.
  • Modeling experience in Computer Vision or  recommendation or  NLP or  RL or  GNN

Preferred Qualifications

  • You should have a proven track record of a leadership role in machine learning , deep learning research and applications demonstrated by patents, publications, product delivery, or other means
  • Experience on performance optimization for Pytorch/TF/MXNet framework, MLPerf benchmark and other SOTA workload
  • Distributed training, Horovod, Torch DDP, Ray SGD
  • Inference optimization such as quantization, sparsity, distillation
  • HPO and NAS algorithm, Bayesian optimization, Optuna, Ray Tune
  • Big data platform, Hadoop, Spark, Modin

Inside this Business Group

Intel Architecture, Graphics, and Software (IAGS) brings Intel's technical strategy to life. We have embraced the new reality of competing at a product and solution levelnot just a transistor one. We take pride in reshaping the status quo and thinking exponentially to achieve what's never been done before. We've also built a culture of continuous learning and persistent leadership that provides opportunities to practice until perfection and filter ambitious ideas into execution.

Other Locations

US, Oregon, Hillsboro

Posting Statement

All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.

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Machine Learning Software Engineer

Santa Clara, CA 95050

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