Job Description
Are you ready to define the technological landscape of 2026? Nexus 2026 is at the forefront of next-generation AI innovation, building scalable neural architectures that power the future. We are seeking a visionary Lead AI Research Engineer to join our elite engineering team in San Francisco.
In this pivotal role, you will bridge the gap between theoretical research and production-level deployment. You will be responsible for pioneering algorithms that push the boundaries of machine learning, ensuring our systems are not only cutting-edge but also robust, ethical, and scalable. If you thrive in a fast-paced, high-impact environment and want to leave a lasting legacy in the tech industry, we want to hear from you.
Why Join Nexus 2026?
- Work on projects that matter: Revolutionize how AI interacts with the digital world.
- Competitive compensation: $180k - $260k base salary plus equity package.
- Flexible work environment: Hybrid model based in the heart of San Francisco.
- Top-tier talent: Collaborate with the brightest minds in the industry.
Responsibilities
- Research & Development: Design, implement, and optimize novel deep learning algorithms and models focused on Large Language Models (LLMs) and generative AI.
- Production Engineering: Translate research findings into production-ready code, ensuring high performance, scalability, and reliability.
- Model Optimization: Conduct extensive experimentation to reduce inference costs and improve model latency across various hardware architectures.
- Mentorship: Lead and mentor a team of junior engineers and data scientists, fostering a culture of innovation and technical excellence.
- Cross-Functional Collaboration: Partner with product managers and engineering teams to define technical roadmaps and solve complex business problems.
- Paper Publications: Author and publish research papers in top-tier conferences (NeurIPS, ICML, ICLR) to establish thought leadership.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Mathematics, or a related field with a focus on Artificial Intelligence, Machine Learning, or Statistics.
- Experience: 5+ years of professional experience in AI/ML engineering, with at least 2 years in a leadership or senior individual contributor role.
- Technical Skills: Strong proficiency in Python, PyTorch, TensorFlow, and SQL.
- Core Knowledge: Deep understanding of deep learning architectures (CNNs, RNNs, Transformers), NLP, and Reinforcement Learning.
- Problem Solving: Demonstrated ability to tackle complex, unstructured problems and deliver scalable solutions.
- Communication: Excellent verbal and written communication skills, with the ability to present technical concepts to non-technical stakeholders.