Job Description
Join the Architects of Tomorrow
Nexus Horizon Labs is at the forefront of defining the technological landscape for the year 2026 and beyond. We are seeking a visionary Senior AI/ML Engineer to lead our Future Tech division. In this role, you won't just be building models; you will be architecting the fundamental intelligence that will power the next generation of global systems.
As we look toward 2026, we need a leader who can bridge the gap between theoretical research and scalable production engineering. You will work in a high-performance environment focused on Large Language Models (LLMs), autonomous agents, and ethical AI infrastructure.
Why join us?
- Shape the future of technology with a team of world-class engineers and researchers.
- Competitive compensation and equity packages designed for high-impact contributors.
- Flexible hybrid work model based in the heart of San Francisco.
- Access to cutting-edge hardware and compute resources.
Responsibilities
- Architect Scalable AI Systems: Design and implement robust machine learning pipelines and infrastructure capable of handling petabyte-scale data and real-time inference.
- Pioneer Future Models: Lead the research and development of next-generation AI models, focusing on efficiency, accuracy, and novel architectures.
- MLOps Leadership: Establish and maintain CI/CD pipelines for ML models, ensuring rapid deployment, monitoring, and automated retraining strategies.
- Ethical AI Compliance: Ensure all deployed models adhere to strict ethical guidelines, bias mitigation protocols, and regulatory standards.
- Cross-Functional Collaboration: Partner with product managers, data scientists, and security teams to translate complex technical requirements into actionable solutions.
- Technical Mentorship: Mentor junior engineers and researchers, fostering a culture of continuous learning and innovation within the Future Tech division.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, Statistics, or a related field.
- Experience: Minimum of 5-7 years of professional experience in machine learning, deep learning, or artificial intelligence engineering.
- Core Skills: Proficiency in Python, PyTorch, or TensorFlow; extensive experience with distributed computing frameworks (e.g., Kubernetes, Apache Spark).
- Model Expertise: Strong background in NLP, Computer Vision, or Reinforcement Learning, with a focus on LLMs.
- Problem Solving: Proven track record of optimizing model performance and reducing inference latency in production environments.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders.