Deep Learning Engineer 2461 views

This is a post on behalf of the AIPlus hiring partner.

Apply with Job ID # 100054

Our partner is the world’s premier AI and data science platform. As a Deep Learning Engineer on their Core Modeling team, you will work on their machine learning platform and actively contribute to the development of their state-of-the-art preprocessing and modeling capabilities. Core Modeling owns the entire data science backend and is responsible for making sure their models and modeling automation are the best in the world. This leading AI/ML Company has just raised its Series E Funding and is poised for growth in 2021!

They are looking for talented people with excellent engineering skills and deep knowledge of Machine Learning who can analyze problems, develop innovative solutions, and implement them for real-world use on top of their platform.
The company is based around delivering best-in-class data science solutions and this position provides the opportunity to build the key data science components of their system focusing on Deep Learning.

Responsibility:

• Automate machine learning processes
• Design and build machine learning models for scalability and accuracy
• Work on development in the following areas: Image/Video, Text, and Audio processing

Main Requirements:

• 3-5 years of combined python Engineering / Data Science experience
  • Minimum 1 year of Engineering experience
  • Minimum 1 year of Data Science experience
  • Minimum 1 year of Deep Learning experience
• Must be a US person

Desired Skills:

• Experience writing maintainable, testable, production-grade Python code
• Good command of scientific Python toolkit (NumPy, scipy, pandas, scikit-learn)
• Understanding of different machine learning algorithm families and their tradeoffs (linear, tree-based, kernel-based, neural networks, unsupervised algorithms, etc.)
• Understanding of time, RAM, and I/O scalability aspects of data science applications (e.g. CPU and GPU acceleration, operations on sparse arrays, model serialization and caching)
• Software design and peer code review skills
• Experience with automated testing and test-driven development in Python
• Experience with Git + GitHub
• Comfortable with Linux-based operating systems
• Proficiency in Deep Learning Frameworks( Keras, Tensorflow, Pytorch, Caffe, Mxnet, etc.)

Plus:

• Experience in semi-supervised/transfer learning
• Experience working in image/video processing, NLP, time-series signal processing, or audio processing is a plus
• Contribution to open-source data-science/deep-learning packages
• Competitive machine learning experience (e.g. Kaggle)
• Previous experience in deploying and maintaining machine learning models in production