Data Science Specialist

Job Description

Designing, analysing and implementing novel, state of the art Machine/Deep Learning models under a dedicated H/W environment. The job includes understanding of models to the level of being able to break it down functionally and map it on a groundbreaking H/W architecture.

Key Responsibilities

  • Research emerging ML/Deep Learning/Data Science solutions and be conversant with the latest developments in the field
  • Prototype and implement novel, state of the art Machine Learning models for Big Data, Computer Vision, NLP & Recommendation Systems
  • Develop advanced modeling capabilities under dedicated H/W environment and identify key strengths in H/W for said models and algorithms
  • Optimise accuracy and speed of algorithms for a massive parallel architecture
  • Prepare reports and presentations for internal and external purposes, and as applicable, jointly co-author publications in peer-reviewed journals and conferences
  • Attend, publish, and present novel research contributions at technical conferences, workshops, and meetups

Requirements:

  • 4+ years experience and deep understanding of machine learning/deep learning, neural networks, statistical classification, and related techniques with their underlying theory and math
  • Practical, hands on, experience in architecting, training and analyzing deep learning models (Convolutional/Recurrent Networks) for image/video and text on large scale data sets
  • Proficient in Python.C/C++, Tensorflow or other Deep Learning frameworks
  • Additional experience with GPU programming for training deep learning models, and cloud environments such as AWS, Azure is desirable
  • Full stack experience in big data processing, aggregation, analysis and visualisation
  • Team player with strong communication skills

Advantage:

  • Proven track record of publications in relevant conferences (CVPR, ICML, NIPS…)
  • Kaggle competition experience
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