This is an amazing opportunity to join a digital team in UAE as a Machine Learning Engineer in Abu Dhabi, UAE for a Ed-tech start-up.
The company has designed a revolutionary digital K12 educational framework that is powered by a 9 layered technology stack which includes Artificial Intelligence, Natural Language Processing and Hyper-interactive media (VR and AR) built to create a much more effective and streamlined educational environment for students. Backed by a large Financial Group they are now implementing a Global Recruitment drive for a talented Machine Learning Engineer to join their team in Abu Dhabi.
Roles and responsibilities:
- Design and prototype algorithms that run on cloud based big data environments.
- Develop feature specifications and performance metrics to capture requirements
- Assemble representative data sets and use them to train and test new algorithms.
- Document designs and report results to product management on a regular basis
- Identify opportunities for new algorithms and hardware improvements for future products.
- Develop and maintain data infrastructure systems that power statistical and machine learning models on large-scale datasets.
- Own data quality throughout all data lifecycles, including acquisition, cleaning, processing, and validation.
- Build platforms to facilitate the rapid iteration of machine learning and optimization algorithms.
- Work closely with Data science and Data engineering teams.
- Identify new ideas to build and evolve Machine Learning solutions, develop new features and benchmark possible solutions.
- Understand algorithms (be able to tweak them when needed) as well as infrastructure that enables fast iterations
- Experienced user of libraries such as scikit-learn, scipy, R, NetworkX, Spacy, and NLTK.
- Working experince of deep learning algorithms and workflows, and experience with any of the frameworks like Torch, Caffe, MXNet, TensorFlow.
- Knowledge in Spark, Hive, Cassandra, Kafka and NoSQL databases is plus
- Ability to meaningfully present results of analyses in a clear and impactful manner
- Hands on experience with Python, R, Scala, Java
- Exposure to machine learning frameworks: Tensorflow, Keras, Pytorch, MXNet
- First-hand experience with a variety of machine learning and pattern recognition techniques
- Develop in Jupyter (IPython) notebook, Spyder and various IDE
- Engineer new features to improve algorithm predictions
- Experience in productionizing data-driven algorithms
- 5 + years of strong data analysis skills, including principal component analysis, working with Recurrent neural networks
- Intuitive ability to see a complex problem from many perspectives
- Organized, detail-oriented and pragmatic
- Thrives in both independent work and in collaboration on a multi-disciplinary team
- Experience in working on datasets related to industry verticals, preferably Education Science
- AWS or similar cloud platform exposure
- Experience working with educational data sets.
- Excellent communication skills.