Job Description
Join the Future of Intelligence
Are you a visionary engineer ready to define the technological landscape of 2026? Nexus Horizon is seeking a Senior AI/ML Engineer to spearhead our next-generation generative AI initiatives. In this pivotal role, you will bridge the gap between theoretical research and scalable production systems, building the models that will power the next decade of digital interaction.
We are not just building software; we are architecting the future. If you are passionate about Large Language Models (LLMs), Computer Vision, and ethical AI development, we want to hear from you.
What You Will Do:
Why Join Us?
- Impactful Work: Deploy models that directly influence millions of users globally.
- Future-Proof Career: Work on cutting-edge tech stacks designed for 2026 and beyond.
- Competitive Compensation: Top-tier salary and equity packages.
Responsibilities
- Model Architecture: Design, train, and fine-tune state-of-the-art deep learning models, specifically focusing on LLMs and Transformer architectures.
- Research & Development: Stay ahead of the curve by exploring novel architectures and methodologies that push the boundaries of current AI capabilities.
- Production Deployment: Optimize models for low-latency inference and high-throughput environments using cloud-native infrastructure (AWS, GCP, or Azure).
- Collaboration: Partner with product managers and data scientists to translate business requirements into technical AI solutions.
- Mentorship: Guide junior engineers and researchers, fostering a culture of innovation and technical excellence within the team.
- Optimization: Implement rigorous testing pipelines and A/B testing strategies to continuously improve model performance and accuracy.
- Security & Ethics: Ensure all deployed models adhere to strict data privacy standards and ethical AI guidelines.
Qualifications
- Education: Master’s or PhD in Computer Science, Machine Learning, Mathematics, or a related field (or equivalent practical experience).
- Programming: Proficiency in Python and C++ with deep knowledge of PyTorch or TensorFlow.
- Experience: 5+ years of professional experience in machine learning engineering or applied research.
- Frameworks: Extensive experience with Hugging Face, LangChain, or similar LLM frameworks.
- Tools: Strong command of Docker, Kubernetes, and CI/CD pipelines.
- Problem Solving: Demonstrated ability to troubleshoot complex distributed systems and optimize training workflows.
- Communication: Excellent verbal and written communication skills, capable of explaining complex technical concepts to non-technical stakeholders.