Job Description
We are on the precipice of a technological singularity, and Apex Horizon Systems is leading the charge. We are seeking a visionary 2026 AI Strategist & Lead Engineer to architect the foundational models that will redefine human-computer interaction in the coming decade.
In this role, you won't just be writing code; you will be defining the roadmap for artificial intelligence evolution. You will work at the intersection of deep learning, generative AI, and scalable infrastructure, ensuring our solutions are robust, ethical, and future-proof for the 2026 landscape and beyond.
Why Join Us?
- Work on mission-critical projects that impact millions.
- Access to state-of-the-art compute resources and proprietary datasets.
- Competitive equity package and top-tier benefits.
- A culture that prioritizes innovation, autonomy, and technical excellence.
Responsibilities
- Architect Future-Proof AI Systems: Design and implement scalable machine learning architectures tailored for high-volume, low-latency environments required for 2026 applications.
- Lead the 2026 Roadmap: Spearhead the development of proprietary Large Language Models (LLMs) and predictive algorithms that set industry standards.
- Optimize Neural Networks: Continuously refine model accuracy and efficiency, pushing the boundaries of what is possible with current hardware constraints.
- Technical Mentorship: Cultivate a high-performance engineering culture by mentoring junior developers and conducting advanced code reviews.
- Cross-Functional Collaboration: Partner with product managers, designers, and data scientists to translate complex technical requirements into user-centric solutions.
- Ethical AI Governance: Implement robust guardrails and safety protocols to ensure AI outputs are fair, transparent, and compliant with global regulations.
Qualifications
- Proven Expertise: 7+ years of professional experience in software engineering, with at least 4 years specifically focused on AI/ML and deep learning.
- Technical Proficiency: Deep knowledge of Python, PyTorch, or TensorFlow, along with experience in distributed computing systems (Kubernetes, AWS, or GCP).
- Model Engineering: Strong understanding of transformer architectures, fine-tuning strategies, and MLOps pipelines.
- Problem Solving: Demonstrated ability to solve complex, ambiguous problems with innovative technical solutions.
- Leadership Skills: Proven track record of leading technical teams and driving projects from conception to deployment.
- Education: Bachelor’s degree in Computer Science, Mathematics, or a related field; Master’s degree preferred.