Job Description
Are you ready to define the technology of tomorrow? Nexus Horizon is seeking a visionary Senior AI/ML Engineer to lead our cutting-edge initiatives for the 2026 roadmap. We are building the infrastructure for the next generation of generative intelligence, and we need a technical leader who thrives in ambiguity and innovation.
In this pivotal role, you will bridge the gap between theoretical AI research and scalable production systems. You will work directly with our product and engineering leadership to ensure our solutions are not just current, but future-proof. If you are passionate about the ethical and technical evolution of AI, this is your opportunity to shape the digital landscape of 2026.
Responsibilities
- Architect & Build: Design and implement state-of-the-art machine learning models and pipelines that scale to millions of users.
- 2026 Roadmap: Lead technical strategy for emerging AI trends, specifically focusing on Large Language Models (LLMs) and autonomous agents.
- Optimization: Optimize model inference latency and cost-efficiency to ensure high-performance deployment in cloud environments.
- Research & Development: Stay ahead of the curve by researching new methodologies in deep learning and implementing them into our core stack.
- Mentorship: Guide a team of junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
- Collaboration: Partner with cross-functional teams (Product, Design, Engineering) to translate complex AI capabilities into user-centric features.
Qualifications
- Education: MS or PhD in Computer Science, Machine Learning, or a related quantitative field.
- Experience: 5+ years of professional experience in software engineering and machine learning, with at least 2 years in a lead or senior capacity.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, or JAX. Experience with MLOps tools (Kubeflow, MLflow) is highly preferred.
- Domain Knowledge: Deep understanding of Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning.
- Cloud Expertise: Strong experience deploying models on AWS, GCP, or Azure.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders.