Job Description
We are Nexus Horizon Labs, a pioneering research organization dedicated to defining the technological landscape of the year 2026 and beyond. We are currently seeking a visionary Senior AI & Future Systems Engineer to lead our cutting-edge research division. In this role, you will architect scalable, autonomous systems that bridge the gap between current machine learning capabilities and the sophisticated AI paradigms expected in the near future.
You will work in a high-performance environment focused on Generative AI, Reinforcement Learning, and Next-Gen Neural Interfaces. If you are passionate about building the infrastructure that will define the next era of human-computer interaction, we want to hear from you.
Why Join Nexus Horizon?
- Work on projects that are 3-5 years ahead of the market.
- Competitive equity package and top-tier compensation.
- Access to state-of-the-art hardware and computing clusters.
Responsibilities
- Architect Next-Gen AI Solutions: Design and implement scalable machine learning models capable of handling complex, real-time data streams for autonomous decision-making systems.
- Prompt Engineering & Fine-Tuning: Develop and optimize Large Language Models (LLMs) specifically tailored for enterprise-grade reasoning and task automation.
- System Integration: Oversee the integration of AI models into existing cloud infrastructures and edge computing environments to ensure seamless performance.
- R&D Leadership: Lead internal research initiatives to explore emerging technologies, including Multimodal AI and predictive analytics.
- Code Optimization: Apply advanced optimization techniques to reduce latency and increase the efficiency of deep learning pipelines.
- Cross-Functional Collaboration: Partner with product managers and designers to translate complex technical concepts into user-centric applications.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related technical field.
- Experience: 5+ years of professional experience in software engineering with a focus on Machine Learning or Deep Learning.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, or JAX. Experience with cloud platforms (AWS, GCP, or Azure) is mandatory.
- Modeling: Strong background in Natural Language Processing (NLP) and Generative Adversarial Networks (GANs).
- Problem Solving: Demonstrated ability to troubleshoot complex system bottlenecks and optimize computational performance.
- Communication: Exceptional written and verbal communication skills with the ability to present technical strategies to non-technical stakeholders.