Machine Learning Engineer

2 weeks ago

London, Greater London, United Kingdom reddit Full time

About Reddit

Reddit is a vibrant community of communities, built on shared interests, passion, and trust. It's home to the most open and authentic conversations online. Every day, Reddit users engage in discussions about topics they care about, shaping the internet's largest source of information.

The Ads Retrieval Team Mission

Our team focuses on identifying business opportunities within advertising. We leverage machine learning models and data-driven solutions to optimize candidate sourcing, recommendations, early ranking, and filtering in the upper funnel of ads.

Your Role as a Machine Learning Engineer

As a Machine Learning Engineer on our team, you'll play a crucial role in developing end-to-end ML solutions to deliver the right ad to the right user at the right time. You'll contribute to:

  • Building and refining ads retrieval and early ranking systems using advanced machine learning techniques.
  • Researching, implementing, testing, and deploying innovative model architectures, including information retrieval, ANNs, recommendation systems, and deep neural networks within high-dimensional information systems.
  • Working on large-scale data systems, backend services, and product integrations.
  • Collaborating closely with cross-functional stakeholders across product, engineering, research, and marketing teams.

Who You Are

You possess a strong foundation in applied machine learning models using TensorFlow/PyTorch within large-scale ML systems. You have hands-on experience with the entire machine learning lifecycle, from training and evaluating models to testing and deployment.

  • + years of experience applying machine learning models with TensorFlow/PyTorch in large-scale ML systems
  • + years of end-to-end experience training, evaluating, testing, and deploying machine learning models
  • Proficiency in programming languages such as Java, Python, Golang, C++, or similar, along with statistical analysis.
  • Experience orchestrating complex data pipelines and system engineering on large datasets.
  • Prior experience with information retrieval and recommendation systems.
  • Familiarity with the advertising domain and ML solutions is a plus.

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