Job Description
Are you ready to architect the future of intelligent systems? Nexus Horizon Labs is seeking a visionary Senior AI Architect to lead our next-generation R&D initiatives aimed at defining the technological landscape of 2026 and beyond.
In this pivotal role, you will bridge the gap between theoretical machine learning breakthroughs and scalable production infrastructure. We are building the foundation for a hyper-intelligent future, and you will be the master builder.
Why join us?
- Work on groundbreaking projects that will define the industry standard for 2026.
- Competitive compensation and equity packages.
- Access to cutting-edge hardware and proprietary datasets.
- Collaborate with the brightest minds in AI, Robotics, and Quantum Computing.
Responsibilities
- Architectural Vision: Design and deploy scalable, high-performance AI models capable of processing exabytes of data for our 2026 roadmap initiatives.
- Infrastructure Leadership: Oversee the architectural vision for our proprietary neural network infrastructure, ensuring resilience, low-latency processing, and energy efficiency.
- System Integration: Collaborate with cross-functional teams of data scientists, software engineers, and product managers to translate theoretical research into production-ready applications.
- Ethical AI Governance: Establish and enforce rigorous best practices for ethical AI, bias mitigation, and algorithmic transparency to ensure responsible deployment.
- Cloud & MLOps: Architect robust cloud-native solutions using AWS or GCP, optimizing for cost-efficiency and global scalability.
- Team Mentorship: Guide and mentor a team of senior engineers, fostering a culture of innovation and technical excellence.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related technical field with a focus on Deep Learning.
- Experience: 10+ years of experience in software engineering, with at least 5 years dedicated to AI/ML architecture and leadership.
- Technical Skills: Proficiency in Python, TensorFlow, PyTorch, and modern MLOps tools (Kubernetes, Docker, MLflow).
- System Knowledge: Deep understanding of distributed systems, microservices architecture, and cloud platforms (AWS, GCP, or Azure).
- Leadership: Proven track record of leading high-performing engineering teams and mentoring junior developers.
- Strategic Mindset: Ability to translate complex technical requirements into strategic business outcomes.