Job Description
We are at the forefront of the next technological revolution. Apex Future Systems is seeking a visionary Senior AI Researcher to define the architecture of artificial intelligence for the 2026 era and beyond.
In this pivotal role, you will lead the development of next-generation Generative AI models, pushing the boundaries of natural language processing and multimodal learning. You will work in a high-performance environment, collaborating with elite engineers and data scientists to build scalable, ethical, and transformative AI solutions. If you are passionate about the future of technology and want to shape the intelligence of tomorrow, we want to meet you.
Why join us?
- Work on cutting-edge research with significant real-world impact.
- Competitive compensation and equity packages.
- Flexible remote-first culture with premium San Francisco amenities.
Responsibilities
- Lead Model Architecture: Design and implement state-of-the-art Transformer and LLM architectures optimized for the 2026 computational landscape.
- Research Innovation: Conduct original research in prompt engineering, reinforcement learning from human feedback (RLHF), and efficient inference.
- System Optimization: Oversee the training and fine-tuning of large-scale models, focusing on latency reduction and cost efficiency.
- Collaboration: Partner with product teams to translate complex research into deployable, user-centric AI products.
- Ethical AI: Establish rigorous safety protocols and bias mitigation strategies to ensure responsible AI deployment.
- Knowledge Sharing: Publish papers in top-tier conferences (NeurIPS, ICML, ACL) and mentor junior researchers.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Mathematics, or a related field, with a focus on Machine Learning or Natural Language Processing.
- Experience: 5+ years of professional experience in AI/ML research or engineering, with a strong portfolio of published work.
- Technical Skills: Deep expertise in PyTorch, TensorFlow, and Hugging Face Transformers. Proficiency in distributed training frameworks (Ray, Kubernetes).
- Domain Knowledge: Proven track record of working with Large Language Models (LLMs), Generative AI, or Deep Learning.
- Programming: Exceptional Python programming skills and a solid understanding of software engineering best practices.
- Communication: Ability to explain complex technical concepts to non-technical stakeholders clearly and effectively.