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 build technical conviction for high-impact private AI use cases that can move into production. Lead technical AI discovery workshops, run deep-dive customer assessments of feasibility and enterprise readiness (data, governance, security, infrastructure), and develop technical assets like proofs of concept and reference architectures. Translate qualified opportunities into an engineering blueprint for handoff to Forward Deployed Engineers, while documenting and scaling best practices across industries.

Location: Tokyo, Seoul

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Lead AI discovery workshops with ecosystem partners (including NVIDIA) to identify, validate, and prioritize private AI opportunities.
•Discover and scope high-value AI use cases with enterprise customers that deliver measurable business outcomes and can be deployed in production.
•Evaluate enterprise AI readiness by assessing data architecture, governance, infrastructure constraints, security considerations, and data gravity challenges.
•Develop regional domain leadership as an SME within a specialized regional pod and transfer successful AI patterns across customer segments.
•Build and scale technical assets (proofs of concept, reference architectures, technical demos) and define an engineering blueprint for handoff to FDE teams.

Pay and Benefits

Perks:Paid LeaveRemote WorkWellness StipendPhone Reimbursement

Key Requirements

•Strong technical foundation in data science with comfort working directly with code, APIs, notebooks, development frameworks, and enterprise architectures.
•Practical experience building or supporting AI applications across machine learning, deep learning, computer vision, time-series analytics, predictive modeling, anomaly detection, and generative AI.
•Proven success in technical pre-sales, solution architecture, consulting, customer engineering, or similar roles for 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.
•Experience with Python, APIs, cloud-native architectures, data pipelines, and MLOps (modern AI development ecosystems).

Skills:CommunicationStakeholder management

Tech Stack:PythonAPIsNotebooksCloud-native architecturesData pipelinesMLOpsNVIDIA AI EnterpriseNIMsNeMoRAPIDsMachine learningDeep learningComputer visionTime-series analyticsPredictive modelingAnomaly detectionGenerative AIAgentic systemsSecure AIEnterprise data platforms

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: Tokyo, Seoul

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Lead AI discovery workshops with ecosystem partners (including NVIDIA) to identify, validate, and prioritize private AI opportunities.
•Discover and scope high-value AI use cases with enterprise customers that deliver measurable business outcomes and can be deployed in production.
•Evaluate enterprise AI readiness by assessing data architecture, governance, infrastructure constraints, security considerations, and data gravity challenges.
•Develop regional domain leadership as an SME within a specialized regional pod and transfer successful AI patterns across customer segments.
•Build and scale technical assets (proofs of concept, reference architectures, technical demos) and define an engineering blueprint for handoff to FDE teams.

Pay and Benefits

Perks:Paid LeaveRemote WorkWellness StipendPhone Reimbursement

Key Requirements

•Strong technical foundation in data science with comfort working directly with code, APIs, notebooks, development frameworks, and enterprise architectures.
•Practical experience building or supporting AI applications across machine learning, deep learning, computer vision, time-series analytics, predictive modeling, anomaly detection, and generative AI.
•Proven success in technical pre-sales, solution architecture, consulting, customer engineering, or similar roles for 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.
•Experience with Python, APIs, cloud-native architectures, data pipelines, and MLOps (modern AI development ecosystems).

Skills:CommunicationStakeholder management

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