We aim to close the gap between humans & AI, to better navigate the world around & inside us. Our north star is an extension of self, enabled by new software and hardware.
As a Machine Learning Engineer, you will design & build a new kind of entity—a natural extension of intent and thought. This role is perfect for someone who has developed user-facing products and who cares deeply about human-computer interaction. You should especially consider this role if you are sensitive to the qualitative differences between models.
Responsibilities • Design and improve user-facing model behaviors including personality, memory, and voice expressivity. • Develop infrastructure to rapidly generate synthetic data, employ fine-tuning methods, and evaluate models across qualitative and quantitative metrics. • Optimize inference pipelines for latency and scalability
Qualifications • Strong experience in applied machine learning, including data curation, fine-tuning, and scalable model evaluation • Hands-on experience with LLMs, conversational applications is a major plus • Strong opinions on qualitative differences between models (e.g. Claude Sonnet 3.5 vs. GPT 4.5) • Proficiency in Python, PyTorch, and/or TensorFlow • High independence and comfort with ambiguity • Strong interest in human-computer interaction • Portfolio of prior work is a major plus • Prior hardware experience is not needed or required
Details • $160-200k base • High early-stage equity • Apply here
We aim to close the gap between humans & AI, to better navigate the world around & inside us. Our north star is an extension of self, enabled by new software and hardware.
As a Machine Learning Engineer, you will design & build a new kind of entity—a natural extension of intent and thought. This role is perfect for someone who has developed user-facing products and who cares deeply about human-computer interaction. You should especially consider this role if you are sensitive to the qualitative differences between models.
Responsibilities • Design and improve user-facing model behaviors including personality, memory, and voice expressivity. • Develop infrastructure to rapidly generate synthetic data, employ fine-tuning methods, and evaluate models across qualitative and quantitative metrics. • Optimize inference pipelines for latency and scalability
Qualifications • Strong experience in applied machine learning, including data curation, fine-tuning, and scalable model evaluation • Hands-on experience with LLMs, conversational applications is a major plus • Strong opinions on qualitative differences between models (e.g. Claude Sonnet 3.5 vs. GPT 4.5) • Proficiency in Python, PyTorch, and/or TensorFlow • High independence and comfort with ambiguity • Strong interest in human-computer interaction • Portfolio of prior work is a major plus • Prior hardware experience is not needed or required
Details • $160-200k base • High early-stage equity • Apply here