Job Description
Are you ready to define the technological landscape of the year 2026? Apex Intelligence Systems is seeking a visionary AI/ML Architect to lead our cutting-edge research division. We are building the next generation of autonomous agents and generative intelligence platforms that will redefine human-machine interaction.
In this role, you will bridge the gap between theoretical AI research and scalable production systems. You will be responsible for designing robust architectures that handle millions of concurrent requests while ensuring ethical AI standards and data privacy. If you are a forward-thinker ready to push the boundaries of what is possible, we want to hear from you.
Why join us?
We offer a competitive compensation package, equity options, and a dynamic environment where innovation is not just encouraged—it's mandatory. We are currently investing heavily in Agentic AI and Edge Computing for 2026.
Responsibilities
- Architect Design: Design and implement scalable, fault-tolerant ML infrastructure using cloud-native technologies (AWS/Azure/GCP).
- GenAI Leadership: Lead the research and deployment of Large Language Models (LLMs) and multimodal AI systems.
- System Optimization: Oversee the optimization of model inference latency and resource utilization.
- Team Leadership: Mentor a team of data scientists and ML engineers, fostering a culture of continuous learning.
- Strategic Roadmap: Define the technical roadmap for AI capabilities leading up to 2026.
- Collaboration: Partner with product and engineering teams to translate business requirements into technical solutions.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, or a related field (PhD preferred).
- Experience: 7+ years of experience in software engineering and 4+ years of specialized experience in Machine Learning/AI.
- Technical Stack: Proficiency in Python, C++, PyTorch, TensorFlow, or JAX. Experience with MLOps tools (Kubernetes, MLflow, SageMaker).
- Architecture: Strong understanding of distributed systems, microservices, and high-availability architecture.
- Innovation: Proven track record of delivering complex AI projects from concept to production.