Job Description
We are seeking a visionary AI & Machine Learning Architect to define the technological roadmap for the 2026 horizon. As a leader in the tech space, Apex Innovations is committed to pushing the boundaries of what is possible with Generative AI and Large Language Models. You will not just implement existing technologies; you will architect the infrastructure that will power our next decade of growth.
In this pivotal role, you will bridge the gap between theoretical research and production-grade engineering, ensuring our systems are scalable, secure, and future-proof. If you are passionate about shaping the future of intelligent systems and want to lead a world-class engineering team, we want to hear from you.
Responsibilities
- Architect and Lead: Design and oversee the implementation of scalable AI/ML infrastructure and pipelines for the 2026 product suite.
- Strategic Roadmap: Define the long-term technical strategy for AI integration, ensuring alignment with business goals and industry trends.
- Model Optimization: Lead efforts in fine-tuning and optimizing Large Language Models (LLMs) for specific enterprise use cases.
- Cross-Functional Collaboration: Partner with Product Managers, Data Scientists, and Software Engineers to translate business requirements into technical solutions.
- Team Mentorship: Mentor a high-performing engineering team, fostering a culture of innovation and technical excellence.
- Technical Due Diligence: Evaluate emerging technologies and tools to ensure Apex remains at the forefront of the AI revolution.
Qualifications
- Education: Master’s or Ph.D. degree in Computer Science, Machine Learning, or a related quantitative field.
- Experience: 7+ years of experience in software engineering, with at least 3 years in a senior AI/ML architecture role.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, and modern Deep Learning frameworks.
- LLM Expertise: Deep understanding of Large Language Models, fine-tuning techniques (LoRA, PEFT), and RAG architectures.
- Cloud Mastery: Strong experience deploying models on cloud platforms (AWS, GCP, or Azure).
- Leadership: Proven track record of leading engineering teams and delivering complex technical projects on time.