Job Description
Are you ready to define the future of artificial intelligence? Nexus Core Technologies is seeking a visionary Senior AI Architect to lead our next-generation research and development initiatives. We are not just building software for today; we are engineering the intelligent infrastructure for the year 2026 and beyond. In this role, you will spearhead the design of large-scale, self-evolving AI systems that will revolutionize how enterprises interact with data.
As a key player on our elite R&D team, you will bridge the gap between theoretical machine learning and practical, scalable deployment. You will work with state-of-the-art LLMs, reinforcement learning, and edge computing to build systems that learn and adapt in real-time. If you are passionate about pushing the boundaries of what is possible in AI and want to join a company that values innovation above all else, we want to meet you.
Why join Nexus Core Technologies?
- Work on cutting-edge projects that define industry standards.
- Competitive compensation package with equity options.
- Flexible remote-first work culture.
- Access to the latest hardware and cloud infrastructure.
Responsibilities
- Architect and deploy scalable machine learning pipelines and neural network architectures.
- Lead the research and implementation of next-generation Large Language Models (LLMs) and generative AI solutions.
- Collaborate with cross-functional teams to integrate AI models into production environments efficiently.
- Mentor junior engineers and data scientists, fostering a culture of technical excellence.
- Optimize model performance, reduce latency, and ensure high availability of AI services.
- Stay abreast of the latest advancements in AI research and implement best practices.
- Define technical roadmaps for AI initiatives that align with business goals.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field.
- 5+ years of professional experience in software engineering, with at least 3 years specifically focused on AI/ML.
- Deep proficiency in Python, PyTorch, TensorFlow, or similar ML frameworks.
- Strong understanding of NLP, computer vision, or reinforcement learning.
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Proven track record of deploying production-ready machine learning models.
- Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.