10 hours ago

Applied AI Specialist

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 10 hours agoStatus: Live

Job Summary

Identify, validate, and establish technical conviction for high-impact private AI use cases that can move into production. Lead technical discovery workshops and deep-dive sessions with enterprise customers, assess AI readiness across data, governance, security, and infrastructure, and translate qualified opportunities into an engineering blueprint. Partner with ecosystem providers like NVIDIA and specialized pods to build technical assets, capture best practices, and hand off to Forward Deployed Engineers for delivery.

Location: Sydney, Melbourne

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Lead AI discovery workshops by designing and facilitating highly technical, hands-on sessions with ecosystem providers like NVIDIA to identify and prioritize private AI opportunities.
•Discover and scope high-value AI use cases with enterprise customers, translating needs into AI workloads suitable for production deployment.
•Evaluate enterprise AI readiness by assessing data architecture, governance, security considerations, and infrastructure/data gravity challenges for feasibility.
•Develop regional domain leadership and serve as a subject matter expert within the regional pod, transferring successful AI patterns across customer segments.
•Build technical assets and define an engineering blueprint by producing lightweight PoCs/reference architectures and translating qualified opportunities into requirements and scoped outcomes for handoff to FDE teams.

Pay and Benefits

Perks:Paid LeaveRemote WorkWellness StipendPhone ReimbursementVolunteer Time

Key Requirements

•Strong technical foundation in data science and comfort working directly with code, APIs, notebooks, development frameworks, and enterprise architectures.
•Practical hands-on experience building or supporting AI applications across machine learning, deep learning, computer vision, predictive modeling, anomaly detection, and generative AI.
•Experience in technical pre-sales, solution architecture, consulting, customer engineering, or similar roles focused on discovery, qualification, and design of complex enterprise technology initiatives.
•Ability to assess data quality, governance, security, compliance, operational readiness, and infrastructure constraints for private AI deployments.
•Exceptional ability to communicate with both technical and executive audiences and connect business outcomes to implementation strategies.

Skills:CommunicationWorkshops facilitationStakeholder managementProblem-solvingDocumentation

Tech Stack:PythonAPIsNotebooksMLOpsMachine learningDeep learningComputer visionPredictive analyticsTime-series analyticsAnomaly detectionGenerative AIAgentic systemsNVIDIA AI EnterpriseNIMsNeMoRAPIDsCloud-native architecturesData pipelines

Company Brief

Cloudera

Provides a hybrid data platform for managing, analyzing, and securing enterprise data across cloud and on-premises environments, enabling machine learning, analytics, and data engineering at scale.

Industry: Data Infrastructure

Company Size: Enterprise (1,001+ employees)

Revenue: USD 500M to 1B

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 2008

Glassdoor: 3.8

Website LinkedIn

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Cloudera

10 hours ago

Applied AI Specialist

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 10 hours agoStatus: Live

Job Summary

Location: Sydney, Melbourne

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Lead AI discovery workshops by designing and facilitating highly technical, hands-on sessions with ecosystem providers like NVIDIA to identify and prioritize private AI opportunities.
•Discover and scope high-value AI use cases with enterprise customers, translating needs into AI workloads suitable for production deployment.
•Evaluate enterprise AI readiness by assessing data architecture, governance, security considerations, and infrastructure/data gravity challenges for feasibility.
•Develop regional domain leadership and serve as a subject matter expert within the regional pod, transferring successful AI patterns across customer segments.
•Build technical assets and define an engineering blueprint by producing lightweight PoCs/reference architectures and translating qualified opportunities into requirements and scoped outcomes for handoff to FDE teams.

Pay and Benefits

Perks:Paid LeaveRemote WorkWellness StipendPhone ReimbursementVolunteer Time

Key Requirements

•Strong technical foundation in data science and comfort working directly with code, APIs, notebooks, development frameworks, and enterprise architectures.
•Practical hands-on experience building or supporting AI applications across machine learning, deep learning, computer vision, predictive modeling, anomaly detection, and generative AI.
•Experience in technical pre-sales, solution architecture, consulting, customer engineering, or similar roles focused on discovery, qualification, and design of complex enterprise technology initiatives.
•Ability to assess data quality, governance, security, compliance, operational readiness, and infrastructure constraints for private AI deployments.
•Exceptional ability to communicate with both technical and executive audiences and connect business outcomes to implementation strategies.

Skills:CommunicationWorkshops facilitationStakeholder managementProblem-solvingDocumentation

Company Brief

Cloudera

Provides a hybrid data platform for managing, analyzing, and securing enterprise data across cloud and on-premises environments, enabling machine learning, analytics, and data engineering at scale.

Industry: Data Infrastructure

Company Size: Enterprise (1,001+ employees)

Revenue: USD 500M to 1B

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 2008

Glassdoor: 3.8

Website LinkedIn