Job Description
Join Nexus Future Systems as the Lead Architect for Project 2026, a groundbreaking initiative to redefine the boundaries of artificial general intelligence. We are looking for a visionary engineer with a passion for the future to design the neural architectures that will power the next decade of technological evolution.
As the Lead for Project 2026, you will be at the forefront of innovation, working with a world-class team to build scalable, ethical, and high-performance AI systems. This is not just a job; it is a mission to shape the future.
What You Will Do:
- Architect the core infrastructure for our autonomous reasoning engine.
- Lead the research and development of next-generation Large Language Models (LLMs).
- Define the technical roadmap and best practices for the 2026 initiative.
- Collaborate with cross-functional teams to integrate AI solutions into real-world applications.
- Mentor senior engineers and drive technical excellence across the organization.
Qualifications:
- PhD or Master’s degree in Computer Science, Mathematics, or a related field.
- 10+ years of experience in machine learning, deep learning, or AI engineering.
- Proven track record of leading complex technical projects from conception to deployment.
- Expertise in PyTorch, TensorFlow, and distributed training systems.
- Strong background in NLP, Computer Vision, or Reinforcement Learning.
- Exceptional communication skills and a passion for mentoring others.
Responsibilities
- Architect and deploy scalable machine learning pipelines and AI infrastructure on cloud platforms.
- Lead research initiatives into cutting-edge Generative AI models (LLMs, Diffusion).
- Collaborate with cross-functional teams to translate business requirements into technical solutions.
- Mentor junior engineers and data scientists, fostering a culture of innovation.
- Optimize model inference and training efficiency to reduce latency.
- Ensure ethical AI practices and data governance compliance.
Qualifications
- PhD or Master’s degree in Computer Science, Machine Learning, or a related field.
- 7+ years of professional experience in AI/ML engineering.
- Strong proficiency in Python, PyTorch, or TensorFlow.
- Extensive experience with Large Language Models (LLMs) and RAG architectures.
- Deep understanding of distributed systems and cloud computing (AWS/GCP).
- Exceptional problem-solving skills and technical leadership abilities.