Job Description
Join the Architects of Tomorrow.
We are seeking a visionary Lead AI Architect to define and execute our technology roadmap for 2026. At NexusCore Dynamics, we aren't just building software; we are engineering the future of human-machine interaction. In this pivotal role, you will lead a world-class team in designing next-generation neural architectures and scalable AI systems that will define the industry standard for the coming decade.
Why Join Us?
- Shape the strategic vision for 2026 and beyond.
- Work with state-of-the-art LLMs and generative models.
- Competitive compensation and equity package.
- Remote-first culture with top-tier benefits.
If you are passionate about pushing the boundaries of artificial intelligence and want to leave a lasting legacy, we want to hear from you.
Responsibilities
- Define and articulate the technical roadmap for NexusCore's AI initiatives leading up to 2026, ensuring alignment with business goals.
- Architect and implement robust, scalable machine learning systems capable of handling massive data throughput.
- Lead a high-performing team of AI engineers and data scientists, fostering a culture of innovation and technical excellence.
- Oversee the research and deployment of cutting-edge Deep Learning models, including Transformers and diffusion models.
- Collaborate with cross-functional product teams to translate complex AI capabilities into user-centric applications.
- Ensure the ethical use of AI, implementing robust governance and safety frameworks.
- Monitor industry trends and emerging technologies to integrate innovative solutions into our product suite.
Qualifications
- Master’s or Ph.D. in Computer Science, Machine Learning, or a related quantitative field.
- Minimum of 7 years of experience in software engineering and machine learning architecture.
- Extensive experience with Python, PyTorch, TensorFlow, and distributed computing frameworks (e.g., Kubernetes, Apache Spark).
- Deep understanding of Large Language Models (LLMs), RAG pipelines, and prompt engineering.
- Proven track record of leading technical teams and managing complex projects from conception to deployment.
- Strong grasp of MLOps practices, including model versioning, monitoring, and CI/CD pipelines.