Job Description
Architect the Future of Intelligence
Join Nexus 2026, a premier think-tank and engineering firm at the forefront of next-generation technology. We are defining the roadmap for 2026, focusing on advanced Generative AI, autonomous agents, and ethical AI frameworks. If you are a technical visionary ready to push the boundaries of what is possible, this is your stage.
Why Join Us?
We offer a competitive compensation package, equity packages, and the opportunity to work on projects that will define the future of human-machine interaction.
Responsibilities
- Lead System Architecture: Design and implement scalable, fault-tolerant AI infrastructure capable of handling petabyte-scale data processing.
- Pioneering Research: Conduct cutting-edge research in Large Language Models (LLMs) and reinforcement learning to drive our 2026 product roadmap.
- Team Leadership: Mentor a high-performing team of ML engineers and data scientists, fostering a culture of innovation and continuous learning.
- Cross-Functional Collaboration: Partner with product managers and domain experts to translate complex requirements into technical solutions.
- Performance Optimization: Continuously optimize model inference speeds and accuracy to ensure real-time responsiveness in critical applications.
- Roadmap Definition: Contribute to the strategic vision of our upcoming technology releases.
Qualifications
- Education: MS or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 8+ years of professional experience in software engineering, with a strong focus on Machine Learning or AI.
- Technical Skills: Proficiency in Python, PyTorch, or TensorFlow. Deep understanding of distributed systems and cloud architecture (AWS/GCP).
- AI Expertise: Proven track record of deploying and optimizing LLMs or Generative Adversarial Networks (GANs).
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders.
- Problem Solving: Demonstrated ability to tackle ambiguous problems and deliver robust solutions under tight deadlines.