Job Description
Shape the Future of Intelligence at NeuroCore Systems
We are on a mission to revolutionize how machines understand the world. As a Senior AI Engineer, you will lead the development of next-generation Large Language Models and neural architectures that power the next decade of technological advancement. Join a team of visionaries in the heart of San Francisco's tech district.
Why Join Us?
- Work on cutting-edge research with a multi-million dollar R&D budget.
- Competitive compensation package and equity opportunities.
- Flexible remote-first hybrid work model.
- Access to the latest hardware and cloud infrastructure.
Key Responsibilities
- Architect and deploy scalable machine learning pipelines using Python and PyTorch.
- Research and implement novel deep learning algorithms to improve model accuracy and efficiency.
- Collaborate with cross-functional teams of data scientists, researchers, and product managers.
- Optimize existing models for production environments, ensuring low latency and high throughput.
- Mentor junior engineers and conduct code reviews to maintain high engineering standards.
Qualifications
- Master’s or PhD in Computer Science, Mathematics, or a related technical field (or equivalent practical experience).
- 5+ years of professional experience in Machine Learning or Artificial Intelligence.
- Strong proficiency in Python, TensorFlow, PyTorch, and SQL.
- Deep understanding of NLP, Computer Vision, or Reinforcement Learning.
- Experience with MLOps tools (Docker, Kubernetes, AWS, GCP).
Ready to build the future? Apply today!
Responsibilities
- Architect and deploy scalable machine learning pipelines using Python and PyTorch.
- Research and implement novel deep learning algorithms to improve model accuracy and efficiency.
- Collaborate with cross-functional teams of data scientists, researchers, and product managers.
- Optimize existing models for production environments, ensuring low latency and high throughput.
- Mentor junior engineers and conduct code reviews to maintain high engineering standards.
Qualifications
- Master’s or PhD in Computer Science, Mathematics, or a related technical field (or equivalent practical experience).
- 5+ years of professional experience in Machine Learning or Artificial Intelligence.
- Strong proficiency in Python, TensorFlow, PyTorch, and SQL.
- Deep understanding of NLP, Computer Vision, or Reinforcement Learning.
- Experience with MLOps tools (Docker, Kubernetes, AWS, GCP).