AI and Machine Learning Researcher

2 days ago


Étreux, Hauts-de-France, United States SimpliSafe Wireless Home Security Full time
About the Role

We are seeking a highly motivated and experienced Machine Learning Scientist to join our growing Engineering team. As a key contributor, you will play a crucial role in developing and implementing cutting-edge machine learning models, with a focus on Natural Language Processing (NLP), Multi-modal Large Language Models (LLMs) and to enhance our products and services.

Responsibilities:
  • Design, develop, and deploy NLP and LLM models to solve real-world problems in the home security domain.
  • Work with key stakeholders to identify key research initiatives that can have impact to business outcomes
  • Collaborate with engineers and product managers to integrate NLP/LLM capabilities into our existing systems.
  • Stay up-to-date on the latest advancements in NLP/LLM and related fields.
  • Contribute to the development of our machine learning infrastructure and tools.
What You'll Need:Qualifications:
  • MS or PhD in Computer Science, Artificial Intelligence, or a related field.
  • 1+ years of experience in developing or fine-tuning and deploying LLM models such as Llama or similar
  • 1+ years of experience in developing and deploying NLP models such as GPT, BERT or VLM models such as CLIP, DINO
  • 3+ years of experience in developing production-grade machine learning solutions
  • Strong understanding of transformer models, deep learning architectures, and statistical modeling techniques.
  • Strong understanding of training techniques for foundational LLM and VLM models
  • Skilled in Python and relevant machine learning libraries (e.g., PyTorch TensorFlow, Keras etc.).
  • Experience with data preprocessing, feature engineering, and model evaluation.
  • Excellent communication and collaboration skills.
  • Ability to work in a fast-paced environment
Bonus Points:
  • Experience with speech recognition, natural language understanding, or natural language generation.
  • Publication in posters, conference proceedings, journal articles, workshops etc.
  • Familiarity with cloud computing platforms (e.g., AWS, GCP).
  • Contributions to open-source NLP/LLM projects.


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