Catena

Machine Learning Engineer, Python

Catena

full-time

Posted on:

Origin:  • 🇺🇸 United States

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Job Level

Mid-LevelSenior

Tech Stack

KerasLinuxPythonPyTorchScikit-LearnShell ScriptingTensorflow

About the role

  • Train and evaluate ML models using common machine learning frameworks in Python. Examples include TensorFlow, Keras, scikit-learn, or PyTorch.
  • Develop and refine NLP pipelines (e.g., tokenization, entity recognition, similarity models).
  • Perform fine-tuning and prompt engineering for LLMs (GPT, Claude, etc.).
  • Create semantic search and recommendation models using vector embeddings and clustering techniques.
  • Conduct experiments, hyperparameter tuning, and performance benchmarking.
  • Collaborate with software engineers to integrate models into backend systems.
  • Prepare clear documentation, model cards, and evaluation reports

Requirements

  • Strong proficiency in Python for machine learning and data processing.
  • Experience with NLP libraries: spaCy, Hugging Face Transformers, gensim, nltk.
  • Comfortable training deep learning models using Keras, TensorFlow, or PyTorch.
  • Ability to design and execute ML experiments, evaluate models, and interpret results.
  • Familiar with version control (Git), shell scripting, and Linux development environments.
  • Basic back end software engineering skills, such as creating and managing endpoints, database services, and task queues.
  • Experience with production environments (e.g., batch inference, model packaging).
  • Experience with MLOps tools (e.g., MLflow, SageMaker, DVC).
  • Contributions to Kaggle competitions, AI research, or open-source ML/NLP projects.
  • Background in classical ML, unsupervised learning, or semantic modeling.
  • Fully remote, must be able to collaborate during EST hours.
  • Work closely with backend/frontend engineers, but not expected to build application UIs.
  • Focused environment for pure AI/ML development, research, and delivery.