Cognitiv

Research Scientist Intern, Machine Learning

Cognitiv

internship

Posted on:

Origin:  • 🇺🇸 United States • California

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Job Level

Entry Level

Tech Stack

AWSCloudGoogle Cloud PlatformHadoopPythonPyTorchSparkSQL

About the role

  • Optimize ML models – Improve predictive accuracy, inference speed, and efficiency in AdTech applications.
  • Experiment & tune – Run hyperparameter tuning, explore new architectures, and fine-tune models to move the needle on key business metrics.
  • Build strong datasets – Help construct and preprocess high-quality training data for ML pipelines.
  • Run experiments – Conduct PyTorch experiments and evaluate results using clear, measurable metrics.
  • Deploy at scale – Collaborate with researchers and engineers to build scalable ML pipelines for smooth deployment and iteration.
  • Stay ahead of the curve – Keep up with deep learning research and propose novel approaches for model improvement.
  • Communicate findings – Present research and experimental outcomes in clear reports that influence decision-making.

Requirements

  • Pursuing or recently completed a Master’s or Ph.D. in CS, Stats, EE, or a related field.
  • Strong grasp of architectures like Transformers and hands-on with PyTorch.
  • Skilled in hyperparameter tuning, loss function design, and optimizing training pipelines.
  • Proficient in Python for data manipulation and ML experimentation.
  • Familiar with techniques like gradient boosting (XGBoost), PCA, and distributed training.
  • Comfortable with AWS/GCP and have some exposure to Spark, Hadoop, or SQL.
  • Strong communicator – Can explain technical results clearly and thrive in a collaborative, fast-paced environment.