Software Engineering Consulting Intern - Machine Learning Specialization

Job Code: SECI-ML-0-000-000-001

What you'll do:  

  • Develop and deploy production-quality machine learning/deep learning technology for natural language processing (NLP).

  • Use Python (NLP) libraries - SpaCy, gensim, and NLTK - to extract and select feature vectors from free-form text.

  • Build robust, lasting, and scalable recommender systems using neural networks and other deep learning tools.

  • Collaborate with other team members to implement CI/CD pipelines and Python unit tests.

Minimum qualifications:

  • Bachelor's degree in Computer Science or a related technical field, or equivalent practical experience.

  • Strong knowledge and proficiency in Python (highly preferred), Ruby, Perl, Smalltalk, Java, C++, Lisp, or Haskell.

  • The capability of building conventional machine learning pipelines with libraries such as scikit-learn, pandas, statsmodels, etc. 

  • The ability to collaborate well and communicate effectively with others.




Preferred qualifications:

  • Experience with deep learning frameworks (e.g., TensorFlow, PyTorch, Caffe) and their high-level APIs (e.g., Keras). 

  • Specific expertise in recommender systems (collaborative filtering, content-based filtering, or hybrid recommender systems). 

  • 2+ years of professional software development experience or project experience. 

  • Examples of your work such as open-source projects, Kaggle contests, GitHub portfolios, etc. 

  • Familiarity with Git, GitLab, or other version control systems.



If interested in applying for this position, please contact and please include the job code in the subject line, and include your resume as a pdf attachment.

 Neuroscience coupled with AI.

 Don't just hire - neurohire!, a tool of neurosyense.