Engineer 2 - Machine Learning

Comcast

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Strong python programming skills
Experience with pytorch or tensorflow
Knowledge of classical ml algorithms
** Comcast is seeking a Machine Learning Engineer to contribute to the development and deployment of machine learning algorithms, focusing on real-world problem-solving through data-driven solutions. The ideal candidate should have solid Python skills and a strong understanding of machine learning fundamentals, with experience in both classical and deep learning techniques. **

Job Summary

  • The role involves designing, developing, and deploying machine learning models across diverse business use cases within a Fortune 50 media and technology leader.
  • Candidates will apply classical ML algorithms and emerging Generative AI technologies like Transformers and LLM-based solutions to solve complex problems.
  • Comcast offers a dynamic environment where employees can fast-forward their careers by working on cutting-edge products that serve millions of customers daily.

Matching Summary

Match Score: 75

** Comcast is seeking a Machine Learning Engineer to contribute to the development and deployment of machine learning algorithms, focusing on real-world problem-solving through data-driven solutions. The ideal candidate should have solid Python skills and a strong understanding of machine learning fundamentals, with experience in both classical and deep learning techniques. **

Skills & Requirements

Must-have

  • Strong Python programming skills
  • Experience with PyTorch or TensorFlow
  • Knowledge of classical ML algorithms
  • Deep learning and GenAI expertise
  • Feature engineering and EDA skills

Nice-to-have

  • Passion for solving real-world problems
  • Understanding of model interpretability tools
  • Ability to work with moderate guidance
  • Collaboration with senior researchers
  • Curiosity about latest ML research

Key Requirements

  • Bachelor's Degree preferred
  • 2-5 years of relevant work experience

Work Rights

Not specified

Tailored Resume

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