Job Description
Are you ready to architect the future? 2026 Systems is a visionary technology firm at the forefront of next-generation artificial intelligence and neural engineering. We are seeking a visionary Senior AI Architect to lead the development of our proprietary quantum-ready neural networks.
In this pivotal role, you will bridge the gap between theoretical machine learning breakthroughs and scalable, production-grade software. You will work alongside a world-class team of researchers and engineers to build the infrastructure that powers the smart cities of tomorrow.
Why Join Us?
- Work on cutting-edge technologies that define the next decade of innovation.
- Competitive compensation package with equity options.
- Flexible remote-first culture with access to top-tier resources.
- Opportunity to mentor the next generation of AI pioneers.
Don't just keep up with the future—help build it.
Responsibilities
- Design and implement scalable, high-performance AI architectures capable of processing exabytes of real-time data.
- Lead the research and development of Generative AI models, focusing on prompt optimization and hallucination reduction.
- Collaborate with cross-functional teams (product, data science, and engineering) to translate complex business requirements into technical blueprints.
- Establish and enforce best practices for code quality, model deployment, and MLOps pipelines.
- Conduct rigorous code reviews and technical mentoring for junior and mid-level engineers.
- Stay ahead of industry trends, evaluating emerging technologies like Neuromorphic computing and Edge AI.
Qualifications
- Master’s degree or Ph.D. in Computer Science, Mathematics, or a related field; equivalent industry experience is highly valued.
- Minimum of 7+ years of professional experience in software engineering, with a strong focus on Machine Learning and Deep Learning.
- Expert proficiency in Python, PyTorch, TensorFlow, and distributed computing frameworks (e.g., Kubernetes, Docker).
- Proven track record of deploying large-scale ML models in production environments.
- Strong understanding of data structures, algorithms, and software design patterns.
- Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.