Analytics

Machine Learning Engineer

We're looking for engineers who are passionate about subject like information retrieval, distributed computing, artificial intelligence and natural language processing.

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Job Details

  • Build cutting-edge Artificial Intelligence and Machine Learning applications
  • Design, development, and testing of (Deep) Machine Learning solutions for Recommendations Engines; Forecasting/Predictive solutions; Image, Voice and video analysis solutions; Reinforcement Learning for Robotics; Chatbots/Conversational Agents
  • Advanced Text Analytics Solutions, Natural Language Processing and Understanding
  • Perform end-to-end design and implementation of data analytics systems; this includes data gathering, requirement engineering, and specification, as well as the conceptualization of technical solutions based on business needs
  • Work closely with other Data Scientists, Data Engineers to identify opportunities for design and implementation of internet scale Data Mining solutions
  • Develop ETL pipelines for large, complex datasets; Processing of structured and unstructured data, using Cloud Native Spark and SQL Services
  • Prototype and implement massive scaled Data Analytics solutions, using cloud big data tools
  • Work with Cloud Native Big Data, ML and AI Services to implement industrialised, robust, massively scalable Big Data and AI Solutions using Cloud Native Managed Services on AWS, MS Azure, and GCP

Basic Qualifications

  • MS degree or equivalent in Computer Science, Engineering, or relevant quantitative disciplines like statistics, operations research, bio informatics, mathematics or physics
  • 1 year of work or educational experience in Machine Learning and Artificial Intelligence
  • 1 year of work or educational experience in filtering, state estimation, statistical modeling, and probability
  • 1 year of relevant experience in data analysis fields (statistics/data science)
  • Experience with one or more general purpose scientific computing languages such as Java, C/C++, Python, Matlab, Scala or R

Preferred Qualifications

  • MS in Computer Science, Electrical Engineering, Artificial Intelligence, Machine Learning or related technical fields
  • Experience with one or more of the following: Natural Language Processing and Understanding, Classification, Pattern Recognition and Recommendation Systems
  • Experience in dealing with large amounts of data, e.g., social network data, scientific data, sensor data, etc
  • Applied machine learning experience on large datasets
  • Proven programmer experience in at least one programming language, such as Java, Scala, C++, or a similar object-oriented language

    • Experience or Knowledge in the following is an advantage:

  • Hadoop, HDFS, Hive
  • Spark, Databricks, EMR, AWS Glue
  • Cloud Platforms (AWS, MS Azure, and Google Computing Engine)
  • Spark ML, H2O, Python ML and Data Science Libs (NumPy, SciPy, Pandas, IPython, Scikit-learn, Keras, TensorFlow)

Your prospects at Qimia Inc.

    Awaiting you is a stimulating and challenging work atmospheres,with flat hierarchies and experienced friendly colleagues. Here at Qimia we put a strong focus on the comprehensive training and education of our Engineers and Data Scientists.

    Topics covered in training:

  • Big Data Science:Python Machine Learning Libs (NumPy, SciPy, Pandas, Jupyter, Scikit-learn, Theano, TensorFlow, NLTK), Spark for Data Mining and Machine Learning (Spark SQL, Spark ML, PySpark)
  • Deep Neural Networks:Feed-Forward neural nets, Convolutional neural nets, Recurrent neural nets, development of production-ready TensorFlow and PyTorch and Keras.
  • Data Science and Machine Learning Essentials:Time Series and Sequential Data processing, Supervised and Unsupervised Machine Learning, Classification, Logistic Regression and Random Forest, Support Vector Machines, K-Nearest Neighbors, Naive Bayes and Gradient Boosting
  • Web and Text Mining:Natural Language Processing and Information Retrieval, Categorizing and automatic Tag/Keyword extraction, Document Classification and Clustering, Entity Recognition, tf-idf, N-grams, word2vec and gensim etc.

    • In our training, we work intensively on current and previous Kaggle competitions in areas of Deep Learning, Predictive Analysis, Recommendation Engines and Natural Language Understanding

Apply now