Job Description
Are you ready to architect the systems that will define the trajectory of artificial intelligence in the coming years? Quantum Horizon Labs is looking for a visionary Senior AI Engineer to lead our research into next-generation generative models and autonomous systems.
In this pivotal role, you won't just be maintaining existing pipelines; you will be building the foundational infrastructure for 2026 and beyond. We are pushing the boundaries of Large Language Models (LLMs), reinforcement learning, and edge computing to solve complex, real-world problems. If you are passionate about the future of tech and want to work in a high-impact environment, we want to meet you.
Why Join Us?
- Work on cutting-edge AI research with a budget and autonomy to innovate.
- Competitive compensation and equity package in a Series B startup.
- Flexible remote-first policy with access to premium co-working spaces in SF.
Your Mission
As our Senior AI Engineer, you will bridge the gap between theoretical research and production-ready applications. You will collaborate with product managers, designers, and data scientists to deploy robust AI solutions that scale.
Responsibilities
- System Architecture: Design and implement scalable machine learning pipelines and data infrastructure optimized for high-performance computing.
- Model Development: Spearhead the development, training, and fine-tuning of state-of-the-art neural networks, focusing on LLMs and Computer Vision.
- Optimization: Drive performance optimization efforts to reduce latency and improve inference speed for real-time applications.
- Research & Prototyping: Stay ahead of industry trends by experimenting with novel algorithms and evaluating emerging technologies for 2026 readiness.
- Collaboration: Work closely with cross-functional teams to integrate AI capabilities into our core product suite.
- Mentorship: Guide junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
Qualifications
- Education: Master’s or PhD degree in Computer Science, Artificial Intelligence, Statistics, or a related quantitative field.
- Experience: Minimum of 5+ years of professional experience in software engineering and machine learning.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX. Strong experience with cloud platforms (AWS/GCP/Azure) and containerization (Docker/Kubernetes).
- Specialization: Deep understanding of deep learning architectures, transformer models, or NLP is highly preferred.
- Problem Solving: Demonstrated ability to tackle complex technical challenges and translate them into elegant, efficient code solutions.
- Communication: Excellent written and verbal communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders.