Job Description
Are you ready to shape the future of intelligence?
We are Apex Neural Systems, a premier research lab and tech powerhouse pioneering the AI infrastructure for 2026 and beyond. We are seeking a visionary Senior Generative AI Engineer to lead the development of next-generation Large Language Models (LLMs) and autonomous agents.
In this pivotal role, you won't just be maintaining legacy systems; you will architect the neural foundations that power the next decade of human-machine interaction. Join us in our mission to build ethical, scalable, and breathtakingly capable AI systems.
Why join us?
- Work on cutting-edge LLMs and multimodal architectures.
- Competitive equity package and top-tier benefits.
- Collaborate with world-class researchers and engineers.
- Remote-first flexibility with a San Francisco hub.
The 2026 Vision: We are moving beyond basic chatbots into Reasoning AI. You will define how our models perceive, reason, and execute complex tasks in real-world environments.
Responsibilities
- Architect and deploy scalable RAG (Retrieval-Augmented Generation) pipelines to enhance model accuracy and reduce hallucinations.
- Lead the fine-tuning and alignment of large language models using proprietary datasets.
- Optimize model inference latency and throughput for edge deployment.
- Implement rigorous testing frameworks and evaluation metrics to ensure model safety and robustness.
- Collaborate with product teams to translate complex AI capabilities into user-facing features.
- Research and prototype novel techniques in prompt engineering and agent-based workflows.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, or a related field.
- 5+ years of professional experience in Machine Learning Engineering, Deep Learning, or NLP.
- Strong proficiency in Python, PyTorch, and TensorFlow.
- Extensive experience working with Transformer architectures and LLMs (e.g., GPT, Llama, BERT).
- Deep understanding of MLOps, data pipelines, and model versioning.
- Experience with distributed computing frameworks (Ray, Spark) is a plus.
- Passion for AI ethics, bias mitigation, and responsible AI development.