Job Description
We are Apex Horizon Labs, a premier think-tank and engineering firm dedicated to defining the technological landscape of the 2026 era. We are seeking a visionary Future Tech Lead to spearhead the architecture of next-generation AI systems. If you are obsessed with the future of machine learning, autonomous agents, and generative intelligence, we want to meet you.
In this role, you won't just maintain existing systems; you will build the foundation for the technology that will define the next decade. You will work at the intersection of theoretical research and scalable production engineering, pushing the boundaries of what is possible.
Responsibilities
- Architect Future-Proof AI Systems: Design and implement scalable machine learning infrastructure capable of handling exabyte-scale data streams and real-time inference.
- Lead Strategic R&D: Drive research initiatives focused on Long Short-Term Memory (LSTM) advancements, Transformer optimizations, and reinforcement learning agents for the 2026 roadmap.
- Model Deployment & Optimization: Oversee the end-to-end lifecycle of AI models, from training in cloud clusters to edge-device deployment, ensuring high throughput and low latency.
- Team Leadership & Mentorship: Cultivate a high-performance culture of innovation, mentoring junior engineers and data scientists on advanced algorithmic strategies.
- Interdisciplinary Collaboration: Partner with product managers, ethicists, and domain experts to align technical capabilities with business goals.
- Ethical AI Governance: Establish frameworks for bias mitigation, transparency, and safety in autonomous decision-making systems.
Qualifications
- Education: Master’s degree in Computer Science, Mathematics, or a related STEM field; PhD preferred.
- Experience: 7+ years of professional experience in machine learning engineering, deep learning, or AI research.
- Technical Stack: Expert proficiency in Python, PyTorch, TensorFlow, and CUDA programming.
- Specialized Knowledge: Deep understanding of Large Language Models (LLMs), Natural Language Processing (NLP), and Computer Vision architectures.
- Cloud Mastery: Strong experience with cloud platforms (AWS/GCP/Azure) and containerization technologies (Docker, Kubernetes).
- Soft Skills: Exceptional problem-solving abilities, strategic thinking, and the ability to communicate complex technical concepts to non-technical stakeholders.