Job Description
Join Project 2026, Apex Systems' premier initiative to define the next generation of artificial intelligence. We are seeking a visionary Senior AI Research Scientist to lead the development of scalable, robust, and ethically-aligned Large Language Models. If you are driven by the challenge of solving complex problems and building systems that will impact millions, we want to hear from you.
In this role, you will operate at the cutting edge of technology, bridging the gap between theoretical research and real-world application. You will define the architectural standards for our AI infrastructure and mentor a team of elite engineers.
Responsibilities
- Lead Research Initiatives: Spearhead the research and development of novel neural network architectures and training methodologies.
- System Design: Architect high-performance, distributed training and inference pipelines capable of handling petabyte-scale data.
- Model Optimization: Implement techniques such as quantization, pruning, and distillation to enhance model efficiency and speed.
- Cross-Functional Collaboration: Work closely with product management and software engineering teams to deploy research findings into production environments.
- Talent Development: Mentor junior researchers and engineers, conducting code reviews, and fostering a culture of technical excellence.
- Documentation: Maintain comprehensive technical documentation and contribute to open-source repositories where applicable.
- Innovation: Stay ahead of the curve by exploring emerging trends in AI, including multimodal learning and reinforcement learning.
Qualifications
- Education: PhD in Computer Science, Machine Learning, Statistics, or a related field (or equivalent industry experience).
- Experience: 5+ years of experience in AI/ML research or a senior engineering role within a high-growth tech environment.
- Programming: Expert-level proficiency in Python, C++, and deep frameworks such as PyTorch or TensorFlow.
- Domain Knowledge: Deep understanding of Natural Language Processing (NLP), Transformer models, and Large Language Model (LLM) fine-tuning.
- Problem Solving: Demonstrated ability to tackle ambiguous problems and derive scalable, data-driven solutions.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders and academic audiences.
- Tools: Experience with cloud platforms (AWS/GCP/Azure) and containerization technologies (Docker/Kubernetes).