Job Description
Apex Future Systems is pioneering the infrastructure for the 2026 era of autonomous intelligence. We are not just building software; we are defining the trajectory of how machines understand and interact with the world. As a Senior AI Research Engineer, you will be at the helm of our flagship Generative AI initiatives, tasked with bridging the gap between theoretical breakthroughs and scalable production deployment.
We are looking for a visionary individual who is obsessed with model efficiency, ethical AI, and the next generation of Large Language Models. If you are driven by the challenge of pushing the boundaries of what is possible in AI and want to shape the roadmap for the coming years, we want to hear from you.
Responsibilities
- Lead Model Development for next-generation Generative AI architectures, focusing on optimization for the 2026 compute landscape.
- Architect Scalable Pipelines utilizing Kubernetes and distributed training frameworks to handle petabyte-scale datasets.
- Conduct Groundbreaking Research in Reinforcement Learning and Multimodal AI to enhance agent autonomy.
- Optimize Inference Latency through aggressive quantization, pruning, and model distillation techniques.
- Drive Ethical Standards by implementing fairness, transparency, and safety guardrails into training loops.
- Collaborate with Product Teams to translate complex research into user-facing features that define the future of enterprise software.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Statistics, Mathematics, or a related field.
- Technical Proficiency: Deep expertise in PyTorch, TensorFlow, or JAX with a proven track record of publishing in top-tier conferences (NeurIPS, ICML, ICLR).
- Experience: 5+ years of experience in AI/ML research or applied engineering in a high-growth environment.
- Programming: Expert-level Python proficiency and experience with C++ for high-performance computing.
- Domain Knowledge: Strong understanding of NLP, Computer Vision, or Reinforcement Learning concepts.
- Soft Skills: Exceptional ability to communicate complex technical concepts to diverse stakeholders and lead technical discussions.