Job Description
Join the Architects of 2026.
Nexus Horizon Labs is seeking a visionary Senior AI/ML Engineer to spearhead the next generation of artificial intelligence. As we look toward the pivotal year of 2026, we are building the infrastructure for a new era of human-machine synergy. You will not just be writing code; you will be defining the trajectory of future technology.
In this role, you will lead the development of autonomous agents, optimize deep learning models, and ensure our systems are scalable for the demands of the future.
Why Join Us?
- Work on cutting-edge generative AI and Large Language Models.
- Competitive compensation package with equity options.
- Flexible remote-first culture with a hub in downtown SF.
- Access to the latest hardware and cloud resources.
Responsibilities
- Architect & Deploy: Design and implement robust, scalable machine learning pipelines and production-grade AI models.
- Model Optimization: Fine-tune large language models (LLMs) and neural networks to achieve peak performance in edge and cloud environments.
- Data Strategy: Lead the strategy for data ingestion, cleaning, and management to fuel our predictive algorithms.
- Future-Proofing: Research emerging technologies (e.g., Quantum AI, Neuromorphic Computing) to integrate into our 2026 roadmap.
- Cross-Functional Leadership: Collaborate with product managers and designers to translate complex AI capabilities into user-friendly applications.
- Ethical AI: Implement guidelines to ensure AI fairness, transparency, and safety in all deployments.
Qualifications
- Education: Master’s degree or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 5+ years of professional experience in Deep Learning, Machine Learning, or Data Science.
- Tech Stack: Proficiency in Python, PyTorch, TensorFlow, or JAX.
- Infrastructure: Strong experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Mathematics: Solid foundation in linear algebra, calculus, and statistics.
- Communication: Ability to explain complex technical concepts to non-technical stakeholders.