Job Description
Are you ready to shape the technological landscape of 2026? Nexus Horizon Labs is seeking a visionary Future Tech Lead to spearhead the development of next-generation Generative AI and Autonomous Systems. In this pivotal role, you will define the architectural roadmaps that will define the future of human-machine interaction, working on projects that are set to revolutionize industries globally.
We are not just looking for engineers; we are looking for pioneers. You will operate at the intersection of deep learning, robotics, and scalable software architecture. If you are driven by the challenge of solving complex problems with code and have a passion for the future of technology, we want to hear from you.
Responsibilities
- Lead R&D Initiatives: Direct the research and development of cutting-edge Generative AI models, including Large Language Models (LLMs) and diffusion models, ensuring scalability and performance.
- Autonomous Systems Architecture: Design and implement the core infrastructure for autonomous agents, focusing on safety, decision-making logic, and real-time processing.
- Tech Stack Definition: Establish and advocate for the adoption of modern, future-proof technologies and frameworks that align with the company's long-term strategic vision.
- Cross-Functional Collaboration: Partner with product managers, designers, and engineers to translate high-level concepts into actionable technical requirements.
- Model Optimization: Continuously monitor, evaluate, and optimize AI model performance to reduce latency and enhance user experience.
- Talent Development: Mentor a high-performing team of AI researchers and software engineers, fostering a culture of innovation and continuous learning.
- Market Analysis: Stay ahead of global tech trends and competitive landscapes to ensure our technology remains at the forefront of the industry.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, Robotics, or a related technical field (equivalent experience accepted).
- Experience: Minimum of 7+ years of experience in software engineering, with at least 4 years specifically focused on Machine Learning and AI systems.
- Technical Expertise: Deep proficiency in Python, PyTorch, TensorFlow, and experience deploying models via Kubernetes or Docker.
- AI Specialization: Proven track record of working with LLMs, NLP, or Computer Vision technologies.
- Problem Solving: Exceptional ability to deconstruct complex problems and devise elegant, scalable solutions.
- Communication: Excellent verbal and written communication skills, capable of articulating complex technical concepts to non-technical stakeholders.
- Innovation: A forward-thinking mindset with a demonstrated history of innovative contributions to previous projects.