Job Description
We are seeking a visionary Senior AI Research Engineer to lead our initiative for the 2026 Horizon. At Quantum Horizon Labs, we are not just building software; we are architecting the cognitive foundation of tomorrow. If you are passionate about pushing the boundaries of Generative AI, Reinforcement Learning, and Cognitive Computing, we want to hear from you.
In this pivotal role, you will bridge the gap between theoretical research and scalable production systems. You will work with a world-class team to develop next-generation models that define the AI landscape of 2026 and beyond. This is an opportunity to have a tangible impact on the future of human-machine interaction.
Why Join Us?
- Work on mission-critical projects that define the future.
- Competitive compensation package and equity options.
- Flexible remote-first culture with state-of-the-art equipment.
- Opportunity to publish research and speak at global conferences.
Responsibilities
- Design and implement novel machine learning architectures tailored for high-scale production environments.
- Lead the research and development of proprietary algorithms, focusing on efficiency and scalability.
- Collaborate with cross-functional teams (product, engineering, and design) to translate research into user-facing features.
- Mentor junior engineers and researchers, fostering a culture of innovation and technical excellence.
- Conduct rigorous testing and evaluation of AI models to ensure accuracy, safety, and robustness.
- Stay abreast of the latest advancements in the AI field and integrate cutting-edge methodologies into our stack.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, or a related field, with a focus on Artificial Intelligence.
- Minimum of 5+ years of professional experience in AI/ML engineering, preferably in a high-growth startup or tech giant.
- Deep proficiency in Python, PyTorch, TensorFlow, or JAX.
- Strong understanding of deep learning principles, NLP, and large language models (LLMs).
- Proven track record of publishing papers or delivering production-grade AI solutions.
- Experience with MLOps, cloud platforms (AWS/GCP/Azure), and containerization (Docker/Kubernetes).