Job Description
Are you ready to architect the future of intelligence? Nexus Horizon is seeking a visionary Senior AI/ML Engineer to lead the development of next-generation generative models and autonomous systems. As we prepare for the transformative technologies of 2026, we need a technical leader who can bridge the gap between cutting-edge research and scalable production environments.
In this role, you will not just build models; you will define the ethical standards and architectural blueprints for the AI of tomorrow. Join us in Silicon Valley's heart and help us push the boundaries of what's possible.
Responsibilities
- Model Development: Design, train, and deploy advanced machine learning algorithms and Large Language Models (LLMs) to solve complex business problems.
- System Architecture: Build scalable, high-performance data pipelines and microservices to support real-time AI inference.
- Research & Innovation: Stay ahead of the curve by integrating the latest research findings in Deep Learning and Neural Networks into our core products.
- Optimization: Continuously optimize model performance for speed, accuracy, and resource efficiency in cloud environments.
- Mentorship: Lead a team of junior data scientists and engineers, fostering a culture of technical excellence and innovation.
- Collaboration: Work closely with cross-functional teams including product managers, software engineers, and ethicists to ensure responsible AI deployment.
Qualifications
- Education: Master’s or PhD degree in Computer Science, Statistics, Mathematics, or a related field.
- Experience: 5+ years of professional experience in machine learning, deep learning, or artificial intelligence.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX. Strong understanding of MLOps practices and cloud platforms (AWS, GCP, or Azure).
- Specialization: Demonstrated experience with NLP, Computer Vision, or Reinforcement Learning is highly preferred.
- Problem Solving: Exceptional ability to debug complex systems and derive actionable insights from large datasets.
- Communication: Excellent verbal and written communication skills with the ability to translate technical concepts for non-technical stakeholders.