Job Description
The Future is Now. Are You Ready to Lead It?
Nexus Horizon Labs is pioneering the next generation of artificial intelligence with our 2026 Horizon Initiative. We are seeking a visionary AI/ML Lead to architect scalable, ethical, and groundbreaking AI systems that will define the technological landscape for the coming decade. If you are passionate about pushing the boundaries of machine learning and want to be at the forefront of innovation, we want to meet you.
In this role, you will not just build models; you will shape the strategy for our long-term AI roadmap, ensuring our solutions are robust, secure, and aligned with the rapid evolution of the 2026 tech ecosystem.
Why Join Us?
- Competitive Compensation: Base salary $180k - $250k DOE.
- Equity Package: Meaningful stake in the company’s future.
- Flexible Work: Hybrid model supporting top-tier talent across the US.
- Cutting-Edge Tech: Work with the latest in LLMs, Neural Networks, and Edge Computing.
Responsibilities
- Architect and deploy state-of-the-art Machine Learning models focused on the 2026 roadmap.
- Lead a team of data scientists and engineers in developing scalable AI infrastructure.
- Define the technical vision for the Horizon Initiative, ensuring ethical AI standards and compliance.
- Collaborate with cross-functional teams to integrate AI solutions into core product workflows.
- Optimize existing models for latency, throughput, and cost-efficiency.
- Mentor junior engineers and establish best practices for AI development and deployment.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field.
- 5+ years of experience in AI/ML engineering, with at least 2 years in a lead or senior role.
- Deep expertise in Python, PyTorch, TensorFlow, or similar ML frameworks.
- Strong background in Natural Language Processing (NLP) and Large Language Models (LLMs).
- Experience with MLOps tools (Kubernetes, MLflow, Docker) and cloud platforms (AWS/GCP/Azure).
- Proven track record of shipping production-grade machine learning systems.