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Information Technology 🏢 Full Time ⭐️ Verified

Lead AI Research Scientist: Project 2026

Nexus Horizon
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
Live Update
20 Mei 2026
Deadline
20 Mei 2027

Job Description

Shape the Future with Nexus Horizon.

We are looking for a visionary Lead AI Research Scientist to join our elite team working on Project 2026. As a premier AI research firm, we are developing the next generation of autonomous decision-making systems that will redefine industry standards. You will not just be writing code; you will be architecting the cognitive backbone of our future products.

Located in the heart of San Francisco, we offer a competitive salary, equity packages, and a culture that prioritizes innovation and impact.

Responsibilities

  • Architect Neural Frameworks: Design and implement scalable, state-of-the-art neural network architectures tailored for Project 2026.
  • Lead Research Initiatives: Spearhead research projects that push the boundaries of Generative AI and Reinforcement Learning.
  • Technical Mentorship: Guide a team of junior researchers and engineers, fostering a culture of continuous learning and technical excellence.
  • Model Optimization: Drive the optimization of model inference speeds and reduce latency in high-throughput environments.
  • Collaboration: Partner with cross-functional stakeholders to translate complex research findings into deployable product features.

Qualifications

  • Education: PhD in Computer Science, Mathematics, or a related quantitative field.
  • Experience: 7+ years of experience in AI/ML research and software development.
  • Technical Proficiency: Deep expertise in Python, PyTorch, TensorFlow, and CUDA programming.
  • System Design: Strong understanding of distributed systems, big data processing (Spark, Kafka), and cloud infrastructure (AWS/Azure).
  • Leadership: Demonstrated ability to lead technical teams and manage project lifecycles from conception to deployment.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning System Architecture Leadership Distributed Systems

Ready to Take This Challenge?

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