Job Description
We are on a mission to democratize Artificial Intelligence and build the infrastructure for the next generation of autonomous agents. NeuralCore AI is seeking a visionary Senior AI Research Scientist to join our elite R&D team in San Francisco. In this role, you will lead the development of cutting-edge Large Language Models (LLMs) and Computer Vision algorithms that power enterprise-grade solutions.
You will work in a high-performance environment focused on innovation, collaborating with world-class engineers and researchers to solve complex problems at the intersection of deep learning, optimization, and scalable architecture. If you are passionate about pushing the boundaries of what is possible in AI and want to make a tangible impact on the industry, we want to hear from you.
Why Join Us?
- Competitive salary and equity package.
- Flexible remote-first policy with a premium SF office for collaboration.
- Unlimited PTO and comprehensive health benefits.
- Access to the latest hardware (NVIDIA H100 clusters) for research.
Responsibilities
- Lead the research and development of novel deep learning architectures, focusing on NLP and Generative AI.
- Design and implement scalable algorithms capable of processing petabytes of data efficiently.
- Conduct rigorous experimentation and evaluation of model performance, including bias detection and fairness metrics.
- Collaborate with the engineering team to translate theoretical research into production-ready software.
- Author and publish high-impact research papers in top-tier conferences (NeurIPS, ICML, ACL).
- Mentor junior researchers and PhD students, fostering a culture of continuous learning and technical excellence.
- Stay abreast of the latest academic advancements and integrate them into our product roadmap.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, Statistics, or a related field with a focus on AI/ML.
- 5+ years of experience in applied research within the AI/ML industry or a top-tier academic institution.
- Strong proficiency in Python, PyTorch, or TensorFlow, with deep understanding of model training and optimization.
- Proven track record of publishing in peer-reviewed venues or delivering production-grade AI systems.
- Expert knowledge of machine learning fundamentals: backpropagation, gradient descent, regularization, and probabilistic models.
- Excellent communication skills, with the ability to explain complex technical concepts to diverse stakeholders.
- Experience with distributed training frameworks (e.g., Ray, DeepSpeed) is a plus.