Job Description
The Future is Now.
Apex Innovations is pioneering the next generation of artificial intelligence infrastructure. As we prepare for the technological landscape of 2026, we are seeking a visionary Senior AI Architect to lead the design and deployment of scalable, high-performance machine learning systems. You will be at the forefront of integrating Generative AI, Large Language Models, and predictive analytics into our core product suite.
In this role, you will not just write code; you will architect the future. You will define the technical roadmap for our AI division, ensuring our solutions are robust, secure, and ready for global scale. If you are passionate about pushing the boundaries of what is possible in AI and want to shape the tools used by millions in the coming decade, this is your opportunity.
Why join us?
- Work with state-of-the-art hardware (NVIDIA H100 clusters).
- Competitive equity package and top-tier compensation.
- Flexible remote-first policy with a collaborative HQ in SF.
- Focus on cutting-edge research with real-world application.
Responsibilities
- Architectural Leadership: Design and implement scalable, fault-tolerant AI infrastructure pipelines capable of processing petabytes of data.
- Model Optimization: Lead efforts in model pruning, quantization, and fine-tuning to maximize inference speed and reduce latency in production environments.
- R&D Strategy: Identify emerging AI trends (e.g., Multimodal Learning, Autonomous Agents) and evaluate their feasibility for integration into our product roadmap.
- Team Mentorship: Guide a team of junior engineers and data scientists, conducting code reviews and technical workshops.
- Collaboration: Partner with product managers and stakeholders to translate complex AI capabilities into user-centric features.
- Security & Compliance: Ensure all AI models adhere to strict data privacy regulations and ethical AI guidelines.
Qualifications
- Education: Master’s degree or PhD in Computer Science, Machine Learning, or a related quantitative field.
- Experience: 7+ years of experience in software engineering, with at least 4 years specifically focused on AI/ML systems architecture.
- Technical Skills: Deep proficiency in Python, TensorFlow, PyTorch, or JAX. Experience with distributed computing frameworks (Kubernetes, Spark, Ray).
- Cloud Expertise: Strong background in cloud platforms (AWS, GCP, or Azure) and MLOps practices.
- Problem Solving: Demonstrated ability to solve complex, ambiguous problems and make data-driven architectural decisions.
- Communication: Excellent verbal and written communication skills, capable of presenting technical concepts to non-technical audiences.