Job Description
We are seeking a visionary Senior AI Architect to spearhead the next generation of intelligent systems at Apex Dynamics. In this pivotal role, you will design and deploy scalable generative AI models that redefine user interaction and operational efficiency. You will work at the intersection of research and engineering, bridging the gap between theoretical machine learning breakthroughs and production-ready applications. Join us to build the future of AI infrastructure in the heart of the tech industry.
Why Join Us?
- Work with state-of-the-art Large Language Models (LLMs) and multimodal architectures.
- Competitive compensation package and equity options.
- Flexible remote-first policy with access to premium tech hubs.
- Opportunity to mentor junior engineers and shape engineering culture.
Responsibilities
- Model Development: Architect and fine-tune proprietary Large Language Models (LLMs) and transformer architectures to meet specific business requirements.
- Infrastructure Design: Design and optimize MLOps pipelines for high-volume inference, ensuring low latency and high availability.
- Collaboration: Partner with product managers and data scientists to translate complex business needs into technical AI solutions.
- R&D: Stay abreast of the latest advancements in AI research (e.g., reinforcement learning from human feedback, vector databases) and evaluate their applicability to our stack.
- Code Quality: Write clean, maintainable, and well-documented code; establish coding standards for the AI engineering team.
- Performance Tuning: Conduct rigorous testing and optimization of model performance, memory usage, and cost efficiency.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field (PhD preferred).
- Experience: 5+ years of experience in software engineering with a focus on machine learning or AI.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX. Deep understanding of NLP concepts and architectures.
- Cloud Mastery: Extensive experience deploying models on AWS, Google Cloud Platform (GCP), or Azure using Kubernetes and serverless architectures.
- Problem Solving: Strong analytical skills with a proven track record of solving complex engineering challenges.
- Communication: Excellent verbal and written communication skills, capable of presenting technical concepts to non-technical stakeholders.