Job Description
We are building the infrastructure for the next era of human-machine collaboration. Nexus Horizon Solutions is seeking a visionary Generative AI & Future Tech Architect to lead our R&D initiatives targeting the 2026 technological landscape. In this role, you will not just implement existing solutions; you will architect the foundational systems for emerging paradigms in Large Language Models (LLMs), Autonomous Agents, and Synthetic Data generation.
Why Join Us?
- Work on cutting-edge projects that define the roadmap for 2026.
- Collaborate with world-class engineers and data scientists.
- Competitive compensation package with equity options.
We are looking for a strategic thinker who combines deep technical expertise with a passion for the future.
Responsibilities
- Architect Next-Gen AI Systems: Design scalable, fault-tolerant architectures for deploying and scaling large-scale generative models in production environments.
- Lead the 2026 Roadmap: Define technical milestones and strategic initiatives for proprietary AI technologies leading up to 2026.
- Optimize Model Performance: Implement advanced fine-tuning, quantization, and inference optimization techniques to reduce latency and cost.
- Ethical AI Implementation: Establish governance frameworks and guardrails to ensure responsible AI deployment and mitigate bias.
- Collaborate with Cross-Functional Teams: Partner with product managers, designers, and engineering leads to translate business requirements into technical specifications.
- Research & Development: Stay at the forefront of industry trends, evaluating new frameworks (e.g., JAX, Rust-based ML tools) to improve our stack.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- Technical Expertise: Extensive experience in Python, PyTorch, TensorFlow, or JAX with a deep understanding of deep learning principles.
- System Design: Proven experience designing high-throughput, distributed systems for machine learning workloads.
- Experience: 5+ years of experience in software engineering or machine learning engineering, with at least 2 years focused on generative models or NLP.
- Problem Solving: Exceptional ability to troubleshoot complex, multi-layered technical challenges.
- Communication: Strong verbal and written communication skills, capable of explaining complex technical concepts to non-technical stakeholders.