Job Description
We are seeking a visionary Future-Readiness AI Architect to lead our research into the technological landscape of 2026 and beyond. At Apex Digital Systems, we don't just adapt to the future; we engineer it. You will be responsible for designing scalable, intelligent systems that define the next era of digital interaction.
In this role, you will bridge the gap between theoretical machine learning breakthroughs and practical, high-impact enterprise solutions. You will work in a dynamic environment where your work directly influences the roadmap for our clients' digital transformation.
Why Join Us?
- Work on cutting-edge Generative AI and LLM technologies.
- Competitive equity package and 401(k) matching.
- Flexible remote-first culture with state-of-the-art office amenities.
Responsibilities
- Architect Scalable Models: Design and deploy large-scale machine learning pipelines optimized for 2026 computational workloads.
- Research & Innovation: Explore emerging AI paradigms, including multimodal learning and autonomous agents, to stay ahead of industry trends.
- Model Optimization: Fine-tune and optimize neural network architectures for high-performance inference on edge devices.
- Collaborative Engineering: Partner with data scientists and software engineers to integrate AI models into robust, secure production environments.
- Roadmap Planning: Define technical strategies and feasibility studies for future AI integrations.
- Performance Analysis: Continuously monitor model accuracy, latency, and cost-efficiency, implementing iterative improvements.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Mathematics, or a related technical field.
- Experience: 5+ years of professional experience in AI/ML engineering, preferably in a fintech or high-growth tech environment.
- Technical Stack: Deep proficiency in Python, PyTorch, TensorFlow, and Hugging Face libraries.
- Specialized Knowledge: Extensive experience with Large Language Models (LLMs), RAG (Retrieval-Augmented Generation), and vector databases.
- Infrastructure: Strong understanding of cloud computing (AWS/GCP) and containerization (Docker/Kubernetes).
- Soft Skills: Excellent communication skills with the ability to translate complex technical concepts for diverse stakeholders.
- Problem Solving: Demonstrated ability to troubleshoot complex algorithmic issues and innovate under pressure.