Job Description
Are you ready to define the technological landscape of 2026?
OmniCore Technologies is at the forefront of the next industrial revolution. We are looking for a visionary Senior AI Architect to lead our cutting-edge research division. In this role, you will not just use existing tools; you will help architect the foundational models and neural architectures that will power the enterprise of tomorrow. Join us in building the systems that will define the future of human-machine interaction.
Why join OmniCore? We offer a competitive benefits package, a remote-first culture with annual team retreats, and the opportunity to work on projects that have a global impact. If you are passionate about pushing the boundaries of Artificial General Intelligence (AGI) and sustainable computing, we want to hear from you.
Responsibilities
- Architectural Leadership: Design and implement scalable, high-performance AI models and neural network architectures tailored for future computing environments.
- Research & Development: Lead internal research initiatives to explore novel approaches in Natural Language Processing (NLP), Computer Vision, and predictive analytics.
- Model Optimization: Collaborate with engineering teams to optimize model inference speed and reduce energy consumption for edge deployment.
- Publish & Patent: Author high-impact research papers and secure patents for proprietary algorithms and frameworks.
- Cross-Functional Collaboration: Partner with product managers and data scientists to translate complex research into viable, deployable products.
- Mentorship: Guide junior engineers and data scientists, fostering a culture of innovation and continuous learning.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related technical field.
- Experience: Minimum of 5+ years of experience in designing and deploying production-level machine learning systems.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, and distributed computing frameworks (e.g., Ray, Kubernetes).
- Domain Knowledge: Deep understanding of transformer architectures, LLM fine-tuning, and reinforcement learning.
- Problem Solving: Demonstrated ability to tackle ambiguous problems and drive solutions from concept to deployment.
- Communication: Excellent written and verbal communication skills, capable of explaining complex technical concepts to non-technical stakeholders.