AI/ML Architect

AI/ML Architect

Location:

Experience:

Join us in shaping the future of enterprise AI. As an AI/ML Architect, you will lead the design and implementation of scalable Generative AI and Machine Learning solutions, driving innovation across diverse environments and architectures. This role combines technical leadership with strategic vision to enable high-performance, secure, and cost-optimized AI systems.

Your Role

You will collaborate with engineering, product, and executive teams to translate complex AI workloads into robust architectures. Acting as a trusted advisor, you will guide customers in leveraging AI accelerators and infrastructure investments for maximum impact.

In this role, you will:

• Design and implement scalable AI/ML architectures for training, fine-tuning, and deploying foundational models.
• Analyze customer profiles, workloads, and compliance requirements to identify bottlenecks and optimize performance.
• Deploy infrastructure across hyperscalers (AWS, Azure, GCP), neoclouds (e.g., Sesterce), and on-prem environments.
• Optimize cost-performance trade-offs across multi-architecture setups including NVIDIA, AMD, Tenstorrent, and other AI accelerators.
• Enhance workload performance using frameworks such as PyTorch, TensorFlow, JAX, Ray, Hugging Face, and Triton.
• Implement automated deployment workflows using Kubernetes, Terraform, Helm, Docker, and CI/CD pipelines.
• Lead architectural workshops, deep dives, and technical discussions to accelerate AI adoption.
• Translate complex AI architectures into clear business outcomes for stakeholders.
• Collaborate with cross-functional teams to align infrastructure and AI strategy with product goals.

Your Profile

Mandatory Skills:

• Advanced proficiency in AI/ML frameworks: PyTorch, TensorFlow, JAX, Ray, Hugging Face, Triton.
• Expertise in infrastructure deployment across AWS, Azure, GCP, Sesterce, and on-prem environments.
• Strong understanding of AI accelerators: NVIDIA, AMD, Tenstorrent, and other hardware architectures.
• Proficiency in containerization and automation tools: Kubernetes, Terraform, Helm, Docker, and CI/CD workflows.
• Ability to design scalable, secure, and compliant AI systems for production use.

Optional Skills:

• Experience as a technical advisor to executives and engineering teams.
• Background in performance tuning and resource orchestration.
• Ability to thrive in fast-paced, evolving environments.
• Familiarity with regulatory requirements and secure AI deployment practices.