AI/ML Advisor

Aurora Talent; Kuala Lumpur; On-site; MYR 250,000 - 420,000; Full time

Job summary

Aurora Talent is seeking a seasoned AI/ML Advisor to drive AI-driven solutions in the Oil & Gas sector. You will bridge business, technology, and industry teams to translate challenges into practical AI opportunities.

You will lead customer discussions, develop SOWs and roadmaps, and mentor a team of AI/ML professionals while shaping the practice’s capabilities and offerings.

Qualifications

• Bachelor's or Master's in CS/AI/Data Science or related.
• 10+ years in AI/ML/Analytics or related field.
• Strong background in customer-facing consulting and advisory services.
• Experience in scoping projects, estimating effort, and engaging senior stakeholders.

Responsibilities

• Advise clients on AI/ML opportunities across Oil & Gas value chains.
• Lead discovery workshops, requirements gathering, and solution definition.
• Define project scope, effort estimates, resources, delivery plans, risks.
• Develop SOWs, architectures, proposals, and implementation roadmaps.
• Mentor and develop AI/ML professionals; drive capability building.
• Support GTM activities, industry engagements, and thought leadership.

Skills

AI/ML consulting

Solution architecture

Pre-sales

Client engagement

MLOps

Python

Education

Bachelor's or Master's in CS/AI/Data Science

Tools

Databricks

Azure

AWS

Google Cloud

Job description

We are looking for a seasoned AI/ML Advisor to drive the identification, development, and implementation of AI-driven solutions within the Oil & Gas industry.

This position will serve as a bridge between business, technology, and industry teams, helping customers translate business challenges into practical opportunities leveraging Artificial Intelligence, Generative AI, Machine Learning, and Advanced Analytics.

Key Responsibilities

Customer Advisory & Business Development

• Partner with customers to understand business challenges, operational requirements, and strategic priorities, and identify opportunities where AI/ML, GenAI, and Advanced Analytics can create measurable value.
• Facilitate customer discovery sessions, workshops, requirements gathering, and solution-definition exercises.
• Evaluate business processes, data availability, technology environments, and organizational readiness to determine suitable AI/ML approaches.
• Advise customers on the application of AI/ML technologies across Oil & Gas business processes and operational environments.
• Collaborate with technical experts, engineers, operational teams, and business stakeholders to identify and prioritize high-impact AI/ML use cases.
• Lead the definition of project scope, effort estimates, resource requirements, delivery plans, assumptions, dependencies, and risks.
• Develop Statements of Work (SOWs), solution concepts, architectures, proposals, implementation roadmaps, and delivery strategies.
• Work closely with sales, consulting, engineering, and delivery teams to develop technical and commercial proposals.
• Define project objectives, deliverables, success measures, governance models, and implementation approaches.
• Build trusted customer relationships and support the identification and development of new AI/ML opportunities.
• Support go-to-market activities, client workshops, industry engagements, and AI/ML thought leadership initiatives.
• Develop reusable AI/ML solutions, frameworks, accelerators, methodologies, and industry-specific offerings.

Technical & Delivery Advisory

• Provide technical and strategic direction throughout the project lifecycle, from solution design through implementation and adoption.
• Review AI/ML solution architectures, models, algorithms, and implementation approaches to ensure quality, scalability, reliability, and alignment with business requirements.
• Guide project teams on AI/ML best practices, MLOps, model lifecycle management, model governance, and Responsible AI.
• Provide oversight on delivery risks, technical issues, dependencies, and stakeholder concerns, supporting effective resolution where required.
• Advise customers and delivery teams on the deployment, adoption, integration, and operationalization of AI/ML solutions.
• Ensure AI/ML initiatives remain focused on measurable business impact and long‑term sustainability.

Leadership & Capability Development

• Lead, mentor, and develop a team of AI/ML, Data Science, and Analytics professionals.
• Establish technical standards, methodologies, development practices, and quality frameworks across the AI/ML practice.
• Drive technical capability‑building through coaching, knowledge sharing, training, and mentoring.
• Contribute to recruitment, onboarding, career development, performance management, and succession planning.
• Encourage innovation, continuous learning, collaboration, and technical excellence across the AI/ML organization.
• Build and strengthen the organization's internal AI/ML capabilities, expertise, and reusable intellectual property.

Skills & Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, Mathematics, Statistics, or a related discipline.
• 10+ years of experience in AI, Machine Learning, Data Science, Advanced Analytics, or related technology fields.
• Strong background in customer‑facing consulting, solution advisory, presales, business development, or solution architecture.
• Proven track record of taking AI/ML initiatives from business opportunity identification and solution design through implementation and adoption.
• Experience in project scoping, effort estimation, resource planning, proposal development, and senior stakeholder engagement.
• Strong knowledge of Artificial Intelligence, Generative AI, Machine Learning, Deep Learning, NLP, Computer Vision, Predictive Analytics, and MLOps.
• Hands‑on experience with Python and modern AI/ML frameworks, tools, and platforms.
• Experience with cloud and data platforms such as Microsoft Azure, AWS, Google Cloud, Databricks, or equivalent technologies.
• Strong understanding of data architecture, data engineering, SQL/NoSQL databases, data platforms, and analytics environments.