Job Description
Are you ready to define the future of intelligence? Nexus Horizon Systems is seeking a visionary Senior AI/ML Engineer to architect the next generation of generative models and scalable AI systems. As we prepare for the technological landscape of 2026, we need a leader who can bridge the gap between cutting-edge research and production-grade infrastructure.
In this role, you will spearhead the development of autonomous agents, advanced Large Language Models (LLMs), and ethical AI frameworks. You will work in a high-performance environment where innovation is not just encouraged—it is the mandate. If you are passionate about building systems that think, learn, and evolve, we want to hear from you.
Why Join Us?
- Work on projects that define the roadmap for 2026 and beyond.
- Competitive compensation package with equity options.
- Flexible remote-first culture with state-of-the-art equipment.
Responsibilities
- Architect & Scale: Design and implement scalable machine learning pipelines and generative AI architectures capable of handling petabytes of data.
- Model Development: Lead the research and deployment of next-generation Large Language Models (LLMs) and multimodal AI systems.
- Optimization: Drive performance optimization strategies to ensure low-latency inference in high-traffic environments.
- Ethical AI: Establish and enforce guidelines for responsible AI development, ensuring fairness, transparency, and safety in AI outputs.
- Team Leadership: Mentor junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
- Collaboration: Partner with product teams to translate complex AI capabilities into user-friendly applications.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, Statistics, or a related field.
- Experience: 5+ years of professional experience in machine learning engineering, with at least 2 years specifically in Generative AI or NLP.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and modern MLOps tools (Kubeflow, MLflow).
- System Design: Strong understanding of distributed systems, cloud architecture (AWS/Azure/GCP), and containerization (Docker/Kubernetes).
- Problem Solving: Demonstrated ability to tackle complex mathematical and engineering challenges.
- Communication: Excellent verbal and written communication skills, capable of presenting technical concepts to non-technical stakeholders.