Machine Learning Engineer

ViaSat-posted 2 months ago
Carlsbad, CA
5,001-10,000 employees
Telecommunications
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Capacity & Demand Data Modelling is driving advances in data science, analysis, and engineering at Viasat and looking for a developer who demonstrates curiosity, adaptability, and enjoys solving tough engineering problems. The team works with customers and stakeholders to help drive business value by building applications utilizing our data and machine learning platforms. This task is an exciting challenge for building solutions starting with research and development following all the way through to engineering and deploying projects into production.

  • Work on a production machine learning application that makes real-time revenue-affecting inferences for the business.
  • Design and implement new features and enhancements to the machine learning application.
  • Provide ongoing support, monitoring, and maintenance of deployed products.
  • Monitor emerging technologies and best practices for potential adoption within the Company.
  • 5+ years of professional software development experience specialized in Machine Learning.
  • A degree in Computer Science, Computer Engineering, Software Engineering, Electrical Engineering, Math, Physics, or related field or equivalent work experience.
  • Strong communication and presentation skills.
  • Ability to work with data science and infrastructure teams to design, implement, and deploy machine learning products.
  • Proven team player with the ability to multi-task in a fast-paced dynamic agile work environment.
  • Advanced proficiency in Python & Machine Learning tools.
  • Ability to work with remote team members across time zones.
  • Travel up to 10%.
  • Strong system, software, and test background including both design and implementation.
  • Strong understanding of probability, statistics, linear algebra, and calculus.
  • Experience with data cleaning, transformation, and feature engineering.
  • Experience with Machine Learning Libraries and Frameworks - TensorFlow and/or PyTorch, scikit-learn, Keras.
  • Knowledge of various machine learning algorithms - (Supervised (regression, classification), unsupervised (clustering, dimensionality reduction), and reinforcement learning etc.).
  • Familiarity with large language models (LLMs) like GPT-3, GPT-4, LaMDA, or similar architectures.
  • Experience with productionized Machine Learning applications.
  • Knowledge of different data formats and sources (e.g., SQL databases, NoSQL databases, cloud storage).
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