Job Description
Join Nexus Horizon Technologies as a Senior AI Architect and help define the technological landscape for the year 2026. We are at the forefront of the AI revolution, building scalable, ethical, and groundbreaking systems that will power the next decade of innovation.
In this pivotal role, you will lead the architectural design of our Generative AI and Large Language Model (LLM) infrastructure. You will work in a fast-paced environment where your code directly impacts millions of users, ensuring our platforms remain at the bleeding edge of artificial intelligence.
Why Join Us?
- Impactful Work: Build core infrastructure for the AI products of tomorrow.
- Competitive Package: Top-tier salary and equity package.
- Future-Ready Culture: Work with a team dedicated to the 2026 strategic roadmap.
Responsibilities
- Architect LLM Solutions: Design and implement scalable distributed systems for training and deploying large-scale machine learning models.
- Optimize Performance: Lead efforts to reduce inference latency and improve model accuracy through advanced engineering techniques.
- 2026 Roadmap: Collaborate with product leadership to define the technical strategy and AI capabilities for our 2026 product releases.
- Code Review & Mentorship: Establish coding standards and mentor junior data scientists and engineers to foster a culture of technical excellence.
- Infrastructure Management: Oversee the deployment of AI models on cloud platforms, ensuring high availability and security.
- Research Integration: Stay ahead of industry trends, integrating cutting-edge research into our production environments.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Mathematics, or a related field with a focus on Artificial Intelligence.
- Experience: Minimum of 5+ years of experience in machine learning engineering, preferably in a high-scale production environment.
- Technical Skills: Deep expertise in Python, PyTorch, TensorFlow, or JAX. Proven experience with Hugging Face, LangChain, or similar LLM frameworks.
- System Design: Strong understanding of distributed systems, microservices architecture, and cloud-native technologies (AWS, GCP, or Azure).
- Problem Solving: Demonstrated ability to tackle complex, unstructured problems and deliver robust, scalable solutions.
- Communication: Excellent verbal and written communication skills with the ability to translate technical concepts to non-technical stakeholders.