Company Overview : We are an innovative AI startup based in with office in NYC & SF, co-founded by industry veterans with extensive backgrounds at leading tech companies.
Our aim is to revolutionize real-time, multi-modal AI communication, creating experiences that feel as natural and engaging as human conversation.
We believe in the transformative potential of Large Language Models (LLMs). These models excel at creating comprehensive world models, making them versatile tools for tasks ranging from tutoring and coding assistance to companionship and therapy.
Their conversational abilities enable them to hold meaningful, extended discussions on virtually any topic, with minimal guidance.
Role Overview : We are seeking a Machine Learning Researcher to join our dynamic and growing team. This role involves developing cutting-edge machine learning and LLM models and deploying them to solve real-world business challenges.
You will be instrumental in building solutions from the ground up, leveraging a modern ML tech stack to create impactful applications.
Responsibilities :
- Develop and enhance machine learning models to drive our AI communication products.
- Design, implement, and evaluate experiments to push the boundaries of current AI capabilities.
- Lead efforts in data collection and generation to support model training and evaluation.
- Optimize model performance for both training and inference in distributed computing environments.
- Collaborate with a cross-functional team of ML, data, and software engineers to integrate AI solutions into production systems.
Requirements :
- Minimum of 3 years of experience in developing and deploying production-level AI systems.
- Proven track record of research excellence, including at least one publication as the first author.
- Deep understanding of LLMs and the ability to build foundational models and implement backpropagation for transformer networks.
- Strong grasp of machine learning fundamentals and experience with distributed training methodologies.
- Proficiency in PyTorch and familiarity with production inference pipelines.
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