Job Description
Join Nexus Horizon Labs as we define the technological landscape for the year 2026. We are looking for a visionary Senior AI Architect to lead our transition into next-generation generative models and autonomous systems. You will be responsible for architecting scalable, secure, and ethical AI infrastructure that powers our future products.
At Nexus Horizon, we don't just predict the future; we build it. If you are passionate about pushing the boundaries of machine learning and have a keen eye for scalable architecture, we want to meet you.
Responsibilities
- Lead Architecture: Design and oversee the implementation of end-to-end AI pipelines, focusing on LLMs, Computer Vision, and predictive analytics.
- Future-Proofing: Identify emerging technologies and frameworks (e.g., Quantum AI integration) to prepare our infrastructure for the 2026 market.
- Team Leadership: Mentor a team of data scientists and ML engineers, fostering a culture of innovation and continuous learning.
- Model Optimization: Drive research into model efficiency, reducing latency and computational costs for real-time applications.
- Ethical AI: Ensure all AI deployments adhere to strict ethical guidelines, bias mitigation protocols, and data privacy standards.
- Collaboration: Partner with cross-functional product teams to translate complex technical requirements into actionable engineering solutions.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 5+ years of experience in software engineering and machine learning, with at least 2 years in a senior architectural role.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, and distributed computing frameworks (Kubernetes, Apache Spark).
- Strategic Thinking: Strong ability to foresee industry trends and align technical roadmaps with long-term business goals.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders.
- Problem Solving: Demonstrated history of solving complex, ambiguous problems in high-pressure environments.