Job Description
Are you ready to architect the intelligence that will define the next decade? Nova Horizon Labs is seeking a visionary Senior AI Engineer to lead our strategic 2026 roadmap. We are not just building software; we are constructing the foundational frameworks for the future of autonomous systems and generative intelligence.
In this pivotal role, you will bridge the gap between theoretical research and production-grade deployment. You will work alongside world-class researchers and engineers to solve complex problems in scalability, latency, and ethical AI. If you are passionate about pushing the boundaries of what is possible in 2026 and beyond, we want to hear from you.
Why Join Us?
- Work on next-generation Large Language Models (LLMs) and multimodal AI systems.
- Competitive compensation package including equity options.
- Flexible remote-first policy with a hub in the heart of San Francisco.
- Access to cutting-edge hardware and proprietary datasets.
Responsibilities
- Architect & Optimize: Design and implement scalable deep learning infrastructure capable of handling petabytes of data for our 2026 product suite.
- Model Training: Lead the training, fine-tuning, and evaluation of state-of-the-art generative AI models.
- Production Deployment: Oversee the MLOps pipeline, ensuring models are deployed efficiently with minimal latency and maximum reliability.
- Ethical AI: Establish and enforce best practices for fairness, transparency, and safety in AI decision-making processes.
- Technical Leadership: Mentor junior engineers, conduct code reviews, and drive technical strategy within the AI division.
- R&D Collaboration: Collaborate with product teams to translate complex research concepts into user-centric features.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Mathematics, or a related field with a focus on Artificial Intelligence.
- Experience: 5+ years of professional experience in AI/ML engineering, specifically with deep learning frameworks.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX. Strong understanding of distributed computing (Ray, Spark) and cloud platforms (AWS, GCP, Azure).
- Model Engineering: Proven track record of deploying models that achieve state-of-the-art performance on industry benchmarks.
- Communication: Excellent written and verbal communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
- Problem Solving: Demonstrated ability to troubleshoot complex system issues and optimize performance under pressure.