Job Description
Are you ready to architect the technological landscape of 2026? At Nexus Horizon Systems, we are building the next generation of autonomous intelligence. We are looking for a visionary Senior AI/ML Architect to lead our R&D division in defining the future of predictive analytics and generative AI.
In this pivotal role, you won't just implement existing models; you will pioneer new architectures designed to scale efficiently in a post-quantum era. Join a team of elite engineers pushing the boundaries of what's possible in artificial intelligence.
Why Join Us?
- Work on cutting-edge models that will define the industry standard for 2026 and beyond.
- Competitive equity package and a culture of radical transparency.
- Top-tier benefits including unlimited PTO and wellness stipends.
What You Will Do:
We are seeking a thought leader who thrives in ambiguity and is driven by the challenge of solving unsolved problems.
Responsibilities
- Architect Scalable AI Systems: Design and deploy robust, scalable machine learning pipelines capable of processing petabytes of real-time data.
- Pioneer New Algorithms: Research and implement novel deep learning architectures, specifically focusing on Transformers and Graph Neural Networks.
- MLOps Leadership: Establish a resilient MLOps infrastructure to ensure model deployment, monitoring, and retraining are seamless and automated.
- Cross-Functional Collaboration: Partner with product managers and data scientists to translate complex business requirements into high-performance technical solutions.
- Code Review & Mentorship: Mentor junior engineers and conduct rigorous code reviews to maintain the highest standards of software engineering.
- Performance Optimization: Continuously optimize model inference speeds and reduce latency to ensure real-time user experiences.
Qualifications
- Education: Master’s degree or PhD in Computer Science, Mathematics, or a related field.
- Experience: 7+ years of experience in software engineering, with at least 4 years focused specifically on AI/ML.
- Technical Stack: Deep proficiency in Python, PyTorch, TensorFlow, and C++.
- Frameworks: Extensive experience with cloud platforms (AWS/GCP) and containerization (Docker/Kubernetes).
- Knowledge: Strong understanding of NLP, Computer Vision, or Reinforcement Learning.
- Soft Skills: Exceptional problem-solving abilities and the communication skills to explain complex concepts to non-technical stakeholders.