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AI/ML Engineering Internship

iCustomer is building a Agentic AI powered decision intelligence platform. 

We have an exciting internship opportunity for a Machine Learning Engineer specialized in NLP, AutoML and LLMs. Reporting to the head of AI, the Machine Learning Engineer will be involved in the whole ML project lifecycle and will be in charge of designing, developing, and deploying ML models

Responsibilities:

  • Develop AutoML systems, with LLM-powered conversational architectures. 
  • Manage the full project lifecycle, including data pre-processing, model prototyping, fine-tuning, evaluation, containerization, optimization, and deployment.
  • Explore new architectures and approaches for enhanced knowledge distillation from customer data, with special focus on LLM chains and agents.

Required qualifications:

  • BSc. in Electrical Engineering, Computer Science, Data Science or a closely related STEM discipline, such as statistics or applied mathematics with specialization in machine learning.
  • Proficient with Python for Data Science, including data analysis, modeling, and visualization.
  • Familiar with Deep Learning frameworks, NLP architectures, and LLMs.
  • Strong communication skills needed to present plans, progress, and results to internal clients and decision-makers.
  • Ability to work in an interdisciplinary and multicultural teaming environment.

Preferred qualifications

  • Familiar with LLM chains and agents.
  • Experience with Linux and Cloud environments
  • Familiar with version control tools

Duration

This internship position will have a duration of 2-3 months, with the possibility of extension based on performance and business needs.

Benefits

  • Gain hands-on experience with real-world LLM projects at a leading-edge Agentic AI startup.
  • Collaborate with seasoned founders and machine learning experts, and learn from their expertise.
  • Contribute to groundbreaking projects that have a tangible impact in the AI space.
  • Receive comprehensive feedback and mentoring tailored to bolster your professional growth in the field of machine learning.