Research Engineer / Applied Scientist, Salesforce Research

Salesforce   •  

Palo Alto, CA

Industry: Technology

  •  

Not Specified years

Posted 69 days ago

This job is no longer available.

As a research engineer at Salesforce Research, your role will be at the intersection of software engineering and research, and may range from implementing novel research models to rapid-prototyping demos that show off applications of deep learning on production data.

You will work closely with research scientists to develop models, prototypes, and experiments that push the state of the art in AI research, paving the way for innovative products for the Einstein AI Platform.

You will have the opportunity to take on real-world problems from Salesforce’s enterprise customers with the latest deep learning models.

You have strong programming skills and a background in one or more of the following domains: deep learning, machine learning, natural language processing, or computer vision, with applications such as: text categorization, text summarization, sentiment analysis, information extraction, question answering, dialogue learning, language and vision, image classification, image segmentation, and object detection.

Responsibilities

  • Participate in cutting-edge research in machine learning and artificial intelligence.

  • Develop solutions for large-scale, real-world problems.

Minimum Qualifications

  • BA/BS degree in Computer Science.

  • Experience with one or more general purpose programming languages including but not limited to: Python, C/C++.

  • Knowledge of linear algebra, calculus, statistics, and machine learning.

Bonus Points

  • MA/MS or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, or related technical field.

  • Practical experience in natural language processing, computer vision, crowdsourcing, or information retrieval.

  • Exposure to industry or academic research, particularly in deep learning, neural networks, or related fields.

  • Experience with one or more deep learning libraries and platforms (e.g., TensorFlow, Caffe, Chainer or PyTorch).

  • Experience with Amazon Web Services and Mechanical Turk.

  • Strong computer systems experience in topics such as filesystems, server architectures, and distributed systems.

  • Experience in GPU programming, data visualization, or web development.

  • JR15798