Job Description
We are seeking a visionary Senior AI Engineer to architect the next generation of intelligent systems. As we look toward 2026, the integration of Artificial Intelligence into core infrastructure is no longer a choice—it is a necessity. At Nexus Horizon Labs, we are building the digital backbone for the future, and we need a technical leader to push the boundaries of what is possible.
In this role, you will lead a high-performance team in developing state-of-the-art Large Language Models (LLMs) and autonomous agents. You will bridge the gap between theoretical research and production-grade deployment, ensuring our solutions are scalable, ethical, and transformative.
Why Join Us?
- Work on projects that define the technological landscape of 2026 and beyond.
- Competitive compensation package including equity.
- Flexible work environment and top-tier benefits.
Responsibilities
- Lead the end-to-end development lifecycle of advanced machine learning models, from research to deployment.
- Architect scalable cloud infrastructure (AWS/GCP) optimized for high-throughput inference.
- Mentor junior engineers and data scientists, fostering a culture of innovation and technical excellence.
- Collaborate with product managers to translate complex business requirements into technical AI solutions.
- Optimize existing models for latency, accuracy, and cost-efficiency in real-world scenarios.
- Stay abreast of the latest academic research and implement cutting-edge techniques such as Reinforcement Learning from Human Feedback (RLHF).
- Ensure compliance with data privacy regulations and ethical AI guidelines.
Qualifications
- Master’s degree or PhD in Computer Science, Mathematics, or a related field.
- Minimum of 5 years of professional experience in machine learning and artificial intelligence.
- Expert proficiency in Python, PyTorch, or TensorFlow.
- Strong understanding of distributed systems, microservices architecture, and containerization (Docker/Kubernetes).
- Experience with large-scale data processing pipelines (Spark, Kafka, or similar).
- Proven track record of deploying production-ready AI applications.
- Excellent communication skills and the ability to articulate complex technical concepts to non-technical stakeholders.