Machine Learning Engineer in Dominion

Closed job - No longer receiving applicants

In Dominion we are looking for professionals to join our full-time team who want to use and grow their IT and business skills and interact with our clients' IT teams.

We are a global Services and Solutions company with 9,000 workers distributed in more than 38 countries serving more than 1,000 clients.

We develop custom software following strict quality standards and agile methodologies. Our goal is to maximize the efficiency of processes through the innovative and intelligent application of technology.

We work in the fields of activity of Technology, Telecommunications, Industry and Energy, and we provide services in B2C environments.

Job functions

  • Consulting with managers to determine and refine machine learning objectives.
  • Designing machine learning systems and self-running artificial intelligence (AI) software to automate predictive models.
  • Transforming data science prototypes and applying appropriate ML algorithms and tools.
  • Ensuring that algorithms generate accurate user recommendations.
  • Turning unstructured data into useful information by auto-tagging images and text-to-speech conversions.
  • Solving complex problems with multi-layered data sets, as well as optimizing existing machine learning libraries and frameworks.
  • Developing ML algorithms to analyze huge volumes of historical data to make predictions.
  • Running tests, performing statistical analysis, and interpreting test results.

Qualifications and requirements

  • +3 year of professional experience in Machine Learning or Quantitative Analisys
  • The engineer should have excellent programming and algorithmic skills.
  • Proficient experience with Python and with Data Processing tools:
    • NumPy, SciPy, Pandas, PyTorch, and Apache Spark. We are especially interested in NumPy.
  • Nice to Have: Previous experience with Bayesian Networks and Probabilistic Inference.
  • In-depth understanding of supervised and unsupervised machine learning algorithms.
  • Big Plus: Knowledge of engineering causal models and convolutional neural networks.
  • Also, it would be great if you have a proven track record of deploying learning algorithms in a production system
  • Speaking English fluently is essential


Fully remote You can work from anywhere in the world.
Informal dress code No dress code is enforced.

Remote work policy

Fully remote

Candidates can reside anywhere in the world.

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