Job Description
We are Nexus Core Systems, a pioneer in next-generation artificial intelligence. We are seeking a visionary Senior AI Engineer to join our elite team in San Francisco and spearhead Project 2026, our ambitious roadmap to revolutionize autonomous systems.
In this high-impact role, you will not just write code; you will architect the neural foundations of the future. You will work closely with world-class researchers and engineers to build scalable, robust, and ethical AI models that push the boundaries of what is possible.
Why Join Us?
- Work on cutting-edge research that defines the technological landscape of 2026 and beyond.
- Competitive compensation package including equity options.
- Flexible remote-first culture with a premium office in the heart of San Francisco.
Key Responsibilities
- Lead the design and implementation of deep learning architectures for autonomous decision-making systems.
- Optimize large-scale neural networks for low-latency, high-throughput inference environments.
- Collaborate with cross-functional teams to translate theoretical research into production-ready software.
- Mentor junior engineers and establish best practices for AI model training and validation.
- Conduct rigorous code reviews and architectural assessments to ensure system integrity.
Qualifications
- Master’s or PhD in Computer Science, Mathematics, or a related quantitative field.
- 5+ years of professional experience in Machine Learning, Deep Learning, or Reinforcement Learning.
- Strong proficiency in Python, PyTorch, or TensorFlow.
- Experience with MLOps, cloud infrastructure (AWS/GCP), and containerization (Docker/Kubernetes).
- Proven track record of deploying models that scale to millions of users.
- Excellent communication skills and a passion for solving complex problems.
Responsibilities
- Lead the design and implementation of deep learning architectures for autonomous decision-making systems.
- Optimize large-scale neural networks for low-latency, high-throughput inference environments.
- Collaborate with cross-functional teams to translate theoretical research into production-ready software.
- Mentor junior engineers and establish best practices for AI model training and validation.
- Conduct rigorous code reviews and architectural assessments to ensure system integrity.
Qualifications
- Master’s or PhD in Computer Science, Mathematics, or a related quantitative field.
- 5+ years of professional experience in Machine Learning, Deep Learning, or Reinforcement Learning.
- Strong proficiency in Python, PyTorch, or TensorFlow.
- Experience with MLOps, cloud infrastructure (AWS/GCP), and containerization (Docker/Kubernetes).
- Proven track record of deploying models that scale to millions of users.
- Excellent communication skills and a passion for solving complex problems.