Job Description
Are you ready to architect the future of artificial intelligence?
Apex Future Systems is pioneering the technologies that will define the 2026 Horizon. We are looking for a visionary Principal AI Engineer to lead our research and engineering efforts, building scalable, ethical, and high-performance AI systems that will power the next decade of innovation.
In this role, you will not just keep up with trends; you will set them. You will be responsible for designing the core architectures of our flagship LLMs and Computer Vision pipelines, ensuring they are robust, secure, and ready for the massive scale required by global enterprises in 2026.
Why join us?
- Impactful Work: Build the foundational models that will change how the world interacts with technology.
- Future-Ready Culture: Work in a forward-thinking environment that prioritizes long-term innovation over short-term gains.
- Top-Tier Compensation: Competitive salary, equity, and comprehensive benefits package.
Key Responsibilities:
- Architect and deploy state-of-the-art Generative AI models, focusing on scalability and inference optimization for 2026 standards.
- Lead a cross-functional team of researchers and engineers to define technical roadmaps and research agendas.
- Implement rigorous testing and evaluation frameworks to ensure model safety, fairness, and regulatory compliance.
- Collaborate with product teams to translate complex AI capabilities into user-centric applications.
- Drive innovation in edge computing and federated learning to enable on-device intelligence.
- Mentor junior engineers and foster a culture of continuous learning and technical excellence.
Qualifications:
- Ph.D. or Master’s degree in Computer Science, Mathematics, or a related field with a focus on Machine Learning/AI.
- Minimum of 8 years of professional experience in designing and deploying large-scale machine learning systems.
- Deep expertise in Deep Learning frameworks such as PyTorch, TensorFlow, or JAX.
- Proven track record of leading complex R&D projects from concept to production.
- Strong understanding of MLOps, cloud infrastructure (AWS/GCP/Azure), and containerization (Docker/Kubernetes).
- Excellent communication skills, with the ability to articulate complex technical concepts to diverse stakeholders.
Skills: Python, PyTorch, TensorFlow, MLOps, AWS, GCP, Docker, Kubernetes, NLP, Computer Vision, Machine Learning Architecture
Responsibilities
- Architect and deploy state-of-the-art Generative AI models, focusing on scalability and inference optimization for 2026 standards.
- Lead a cross-functional team of researchers and engineers to define technical roadmaps and research agendas.
- Implement rigorous testing and evaluation frameworks to ensure model safety, fairness, and regulatory compliance.
- Collaborate with product teams to translate complex AI capabilities into user-centric applications.
- Drive innovation in edge computing and federated learning to enable on-device intelligence.
- Mentor junior engineers and foster a culture of continuous learning and technical excellence.
Qualifications
- Ph.D. or Master’s degree in Computer Science, Mathematics, or a related field with a focus on Machine Learning/AI.
- Minimum of 8 years of professional experience in designing and deploying large-scale machine learning systems.
- Deep expertise in Deep Learning frameworks such as PyTorch, TensorFlow, or JAX.
- Proven track record of leading complex R&D projects from concept to production.
- Strong understanding of MLOps, cloud infrastructure (AWS/GCP/Azure), and containerization (Docker/Kubernetes).
- Excellent communication skills, with the ability to articulate complex technical concepts to diverse stakeholders.