Factored is hiring a
Machine Learning Engineer

Summary

The job is for a Machine Learning Engineer specializing in Language Models (LLMs) at Factored. The role involves designing, implementing, and optimizing NLP solutions, collaborating with software engineers, and conducting research. The position is remote.

Requirements

• 5+ years of experience in machine learning and deep learning, with a focus on NLP
• In-depth understanding of LLMs and their architectures, including hands-on experience with transformer-based models (e.g., BERT, GPT)
• Strong knowledge and practical experience in training Deep Neural Networks
• Strong proficiency in programming languages such as Python, along with experience using libraries and frameworks like TensorFlow, PyTorch, scikit-learn, and NLTK
• 2+ years of experience with Convolutional Neural Networks (CNNs) or Vision Transformers for image processing
• Solid understanding of machine learning principles and techniques, including supervised and unsupervised learning, deep learning, and reinforcement learning
• Experience with cloud computing platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes)
• Familiarity with Ray Serve and openness to adopt other distributed serving technologies (Kubeflow, BentoML, Triton, etc)
• Understanding of distributed systems and their application in machine learning
• Knowledge and practical experience in implementing CI/CD pipelines for machine learning projects
• Strong communication skills in English

Responsibilities

• Design, implement, and train LLMs to address specific NLP tasks such as text generation, sentiment analysis, named entity recognition, text summarization, question answering, and more
• Train LLMs on large-scale datasets using state-of-the-art techniques and frameworks such as TensorFlow, PyTorch, or Hugging Face Transformers
• Conduct research to enhance existing LLMs or develop novel models tailored to specific applications
• Analyze model performance, identify areas for improvement, and iterate on the development process to achieve desired outcomes
• Collaborate with software engineers and developers to deploy LLM-based solutions into production environments