Machine Learning Engineer, Python

Catena

full-time

Posted on: 8/20/2025

Location: 🇺🇸 United States

✨ AI Apply

Mid-LevelSenior

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

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.