Applied AI Specialist, Australia (AI)

Location: Hybrid in Sydney, New South Wales, Australia, with Melbourne, Victoria, Australia also listed; flexible work-from-home policy available.

Company

hirify.global helps large enterprises transform complex data into actionable insights through open-source data and AI platforms.

What you will do

• Lead technical, hands-on AI discovery workshops with enterprise customers and strategic ecosystem partners, including NVIDIA.
• Discover, scope, validate, and prioritize high-value private AI use cases suitable for production deployment.
• Assess data architecture, governance, security, compliance, infrastructure constraints, and data gravity challenges.
• Develop regional domain expertise and transfer successful AI patterns across customers, industries, and regions.
• Build proofs of concept, reference architectures, technical demonstrations, and solution frameworks.
• Define technical requirements, data specifications, success criteria, architectural recommendations, and scoped outcomes for handoff to Forward Deployed Engineer teams.

Requirements

• Strong technical foundation in data science, with hands-on ability to work with code, APIs, notebooks, development frameworks, and enterprise architectures.
• Practical experience with AI applications across machine learning, deep learning, computer vision, time-series analytics, predictive modeling, anomaly detection, and generative AI.
• Ability to discuss model architectures, training and evaluation methodologies, inference patterns, and production deployment considerations across enterprise AI workloads.
• Proven experience in technical pre-sales, solution architecture, consulting, customer engineering, or a similar role involving discovery, qualification, and design of complex enterprise technology initiatives.
• Ability to evaluate data quality, governance, security, compliance, operational readiness, and infrastructure constraints affecting private AI deployments.
• Exceptional communication skills for engaging technical and executive audiences and connecting business outcomes with implementation strategies.
• Experience with Python, APIs, cloud-native architectures, data pipelines, MLOps, and modern AI development ecosystems.

Nice to have

• Experience with NVIDIA AI Enterprise, NIMs, NeMo, RAPIDS, or accelerated computing platforms.
• Experience delivering customer-facing workshops, design sessions, or architecture engagements.
• Experience moving AI projects from proof of concept into production environments.
• Familiarity with enterprise data platforms, governance frameworks, and hybrid cloud architectures.

Culture & Benefits

• Centralized platform support for cloud credentials, environment setup, and workshop preparation.
• Clear operational separation between discovery and qualification work and subsequent implementation by Forward Deployed Engineer teams.
• Access to AI practitioners, strategic ecosystem partners, and enterprise innovators.
• Generous paid time off, unplugged days, flexible work-from-home policy, and work-life balance support.
• Mental and physical wellness programs, phone and internet reimbursement, continued career development, comprehensive benefits, paid volunteer time, and employee resource groups.