Job Description
Welcome to Nexus Future Systems, a pioneer in next-generation artificial intelligence infrastructure. We are embarking on an aggressive roadmap for 2026, aiming to redefine the boundaries of generative intelligence and autonomous decision-making systems.
We are seeking a visionary Lead AI Architect to spearhead our core research and engineering efforts. In this role, you will not just use existing tools; you will help define the architectural standards for the next decade of technology. If you are passionate about scalable AI, ethical machine learning, and building systems that matter, we want you on our team.
Why Join Us?
- Work on high-impact projects that will shape the future of AI.
- Competitive compensation package with equity options.
- Flexible remote-first culture with hubs in SF and NYC.
Responsibilities
- Design and implement robust, scalable machine learning pipelines for the 2026 product suite, focusing on Large Language Models and Computer Vision.
- Lead architectural decisions that balance performance optimization with cost-efficiency and data privacy.
- Establish and enforce best practices for model deployment, monitoring, and MLOps (Machine Learning Operations).
- Collaborate with cross-functional teamsâincluding product managers, data scientists, and engineersâto translate complex business requirements into technical roadmaps.
- Mentor senior and junior engineers, fostering a culture of innovation, continuous learning, and technical excellence.
- Conduct deep-dive research into emerging AI paradigms to integrate cutting-edge advancements into our core stack.
Qualifications
- Masterâs degree or PhD in Computer Science, Artificial Intelligence, Robotics, or a related technical field.
- 7+ years of professional experience in software engineering, with at least 4 years specifically in AI/ML architecture.
- Deep proficiency in Python, PyTorch, TensorFlow, or JAX.
- Extensive experience with cloud infrastructure (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Strong understanding of distributed systems, high-availability architectures, and real-time data processing.
- Proven track record of shipping production-grade AI products to market.