Job Description
We are seeking a visionary Senior AI Research Engineer to lead our next-generation artificial intelligence initiatives. As we prepare for the 2026 technological landscape, you will play a pivotal role in developing scalable, autonomous AI systems that redefine industry standards. You will work at the intersection of machine learning, deep learning, and cloud infrastructure, pushing the boundaries of what is possible with Large Language Models (LLMs) and generative AI.
Why Join Nexus Future Systems?
- Work on cutting-edge projects that will shape the future of the technology sector.
- Competitive compensation package with equity options.
- Flexible remote-first policy with a vibrant office culture in downtown San Francisco.
If you are passionate about the future of AI and want to leave a lasting impact, we want to hear from you.
Responsibilities
- Lead Research & Development: Spearhead the research and implementation of novel neural network architectures designed for 2026 and beyond.
- Model Optimization: Engineer high-performance models that are optimized for low-latency inference and massive scalability.
- Collaboration: Partner with cross-functional teams of data scientists, engineers, and product managers to translate research into production-ready applications.
- System Design: Design robust pipelines for data ingestion, training, and deployment of AI models on distributed cloud environments.
- Ethical AI: Ensure all AI systems adhere to ethical guidelines and mitigate potential biases in algorithmic decision-making.
- Mentorship: Mentor junior engineers and researchers, fostering a culture of innovation and continuous learning within the technical team.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Machine Learning, or a related quantitative field.
- Experience: 5+ years of professional experience in AI research, deep learning, or natural language processing.
- Technical Skills: Proficiency in Python, PyTorch, or TensorFlow; extensive experience with transformer models and LLMs.
- Infrastructure: Strong understanding of cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Problem Solving: Proven track record of solving complex, unstructured problems in high-stakes environments.
- Communication: Excellent written and verbal communication skills, with the ability to articulate complex technical concepts to diverse audiences.