Job Description
The Future is Here. Nexus Future Systems is pioneering the next generation of artificial intelligence. We are seeking a visionary Senior AI Research Engineer to join our 2026 Visionary Track. In this role, you won't just implement existing models; you will architect the algorithms that will define human-machine interaction for the coming decade. If you are driven by complexity, scalability, and the ethical implications of AI, this is your stage.
As a key player in our San Francisco hub, you will bridge the gap between theoretical research and production-grade deployment. You will work with world-class data scientists and engineers to build robust, scalable, and unbiased AI systems that power our global platform.
Why Join the 2026 Visionary Track?
- Impact: Directly influence the roadmap of our flagship AI product.
- Autonomy: Enjoy the freedom to experiment with bleeding-edge research without bureaucratic red tape.
- Compensation: Competitive salary, equity package, and top-tier benefits.
Ready to shape the future? Apply today.
Responsibilities
- Pioneer New Architectures: Design and implement cutting-edge deep learning models, focusing on Large Language Models (LLMs) and generative AI for 2026 readiness.
- Optimize Performance: Engineer high-performance inference pipelines that minimize latency and maximize throughput in production environments.
- Ethical AI Governance: Develop and enforce frameworks for fairness, transparency, and accountability in AI decision-making processes.
- Research Publication: Contribute to top-tier academic conferences and industry journals, establishing Nexus Future Systems as a thought leader.
- Cross-Functional Leadership: Collaborate with product managers and software engineers to translate complex research into tangible user value.
- Data Pipeline Oversight: Ensure the integrity and quality of training data through advanced data cleaning and augmentation strategies.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, Physics, or a related field with a focus on AI/ML.
- Technical Expertise: Deep proficiency in Python, PyTorch, TensorFlow, or JAX with a strong understanding of distributed computing.
- Experience: 5+ years of experience in research engineering, machine learning research, or a similar R&D role.
- Problem Solving: Proven track record of solving complex, open-ended problems in high-scale systems.
- Communication: Excellent verbal and written communication skills, with the ability to explain complex concepts to diverse audiences.
- Tools: Experience with MLOps tools (e.g., Kubeflow, MLflow) and cloud platforms (AWS/GCP/Azure).