Job Description
Are you ready to define the future of Artificial Intelligence? Nexus Future Labs is leading the charge on the 2026 Initiative, a groundbreaking project aimed at revolutionizing human-machine interaction through next-generation neural networks. We are seeking a visionary Senior AI Engineer to join our elite research team in San Francisco.
In this pivotal role, you will architect and deploy scalable machine learning models that push the boundaries of what is possible. You won't just be writing code; you will be building the intelligence infrastructure that will define the industry standard for 2026 and beyond.
Why Join Us?
We offer a competitive compensation package, equity opportunities, and a remote-first culture that empowers creativity. Work alongside the brightest minds in tech to solve humanity's most complex problems.
Key Benefits:
- Competitive Base Salary: $160k - $220k USD
- Comprehensive Health, Dental, and Vision Insurance
- Equity Participation in the 2026 Initiative
- Unlimited PTO and Flexible Remote Work Options
- Access to cutting-edge hardware and cloud infrastructure
Responsibilities
- Architect and implement robust, scalable AI models for the 2026 Initiative, focusing on generative AI and large language models.
- Lead the design of neural network architectures and optimize inference pipelines for high-performance environments.
- Collaborate with cross-functional teams (product, engineering, and ethics boards) to ensure responsible AI deployment.
- Conduct research to stay at the forefront of AI advancements and integrate novel techniques into production systems.
- Mentor junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
- Debug complex system issues and ensure high availability of critical AI services.
Qualifications
- Master’s or PhD degree in Computer Science, Mathematics, or a related field with a focus on AI/ML.
- Minimum of 5 years of professional experience in machine learning, deep learning, or natural language processing.
- Strong proficiency in Python and experience with frameworks such as TensorFlow, PyTorch, or JAX.
- Proven track record of deploying large-scale ML models to production environments (e.g., AWS, GCP, Azure).
- Deep understanding of neural network optimization, distributed computing, and cloud infrastructure.
- Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.