Senior aiml consultant Vacatures

Over de vacature

As a Senior AI/ML Consultant in AWS Professional Services, you will lead the delivery of cutting-edge artificial intelligence and machine learning solutions for our enterprise customers. You'll drive innovation in Artificial Intelligence and Machine Learning, shape technical strategy, and serve as a trusted advisor to customers throughout their AI transformation journey.

Key job responsibilities
1. Lead end-to-end delivery of complex AI/ML engagements, from strategic planning through to pre-production deployment and optimisation
2. Architect and implement advanced solutions leveraging AWS's AI/ML services, with particular focus on Generative AI using Amazon Bedrock and SageMaker
3. Provide technical leadership and mentorship to junior consultants while driving best practices across delivery teams
4. Partner with customers to translate business challenges into measurable ML outcomes and clear delivery roadmaps
5. Drive innovation in applied AI/ML, contributing to methodologies and reusable solutions across the practice
6. Influence customer AI strategy through technical expertise and industry insights
7. Lead multi-disciplinary teams and coordinate across stakeholder groups to deliver high-impact AI solutions
8. Provide thought leadership in internal and external engagements
9. Support pre-sales activities to provide technical expertise and review project scoping and risks

About the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.

Why AWS?
Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture
Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

Mentorship & Career Growth
We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud.
BASIC QUALIFICATIONS - Bachelor's degree, or experience in cloud based solution (AWS or equivalent), system, network and operating system
- Experience as technical specialist in design and architecture
- Experience in consulting, design and implementation of serverless distributed solutions
- Experience in software development with object oriented language
- Experience in data and machine learning engineering and cloud native technologies
- Experience building complex highly-scalable systems that involve predictive models or applications of machine learning
PREFERRED QUALIFICATIONS - Knowledge of AWS services including compute, storage, networking, security, databases, machine learning, and serverless technologies
- Experience in external or internal customer facing, complex and large scale project management
- Experience in database (eg. SQL, NoSQL, Hadoop, Spark, Kafka, Kinesis)
- Experience with Machine and Deep Learning toolkits such as MXNet, TensorFlow, Caffe and PyTorch
- Experience facilitating discussions with senior leadership regarding technical / architectural trade-offs, best practices, and risk mitigation

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( ) to know more about how we collect, use and transfer the personal data of our candidates.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

Over de vacature

As a Senior AI/ML Consultant in AWS Professional Services, you will lead the delivery of cutting-edge artificial intelligence and machine learning solutions for our enterprise customers. You'll drive innovation in Artificial Intelligence and Machine Learning, shape technical strategy, and serve as a trusted advisor to customers throughout their AI transformation journey.

Key job responsibilities
1. Lead end-to-end delivery of complex AI/ML engagements, from strategic planning through to pre-production deployment and optimisation
2. Architect and implement advanced solutions leveraging AWS's AI/ML services, with particular focus on Generative AI using Amazon Bedrock and SageMaker
3. Provide technical leadership and mentorship to junior consultants while driving best practices across delivery teams
4. Partner with customers to translate business challenges into measurable ML outcomes and clear delivery roadmaps
5. Drive innovation in applied AI/ML, contributing to methodologies and reusable solutions across the practice
6. Influence customer AI strategy through technical expertise and industry insights
7. Lead multi-disciplinary teams and coordinate across stakeholder groups to deliver high-impact AI solutions
8. Provide thought leadership in internal and external engagements
9. Support pre-sales activities to provide technical expertise and review project scoping and risks

About the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.

Why AWS?
Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture
Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

Mentorship & Career Growth
We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud.
BASIC QUALIFICATIONS - Bachelor's degree, or experience in cloud based solution (AWS or equivalent), system, network and operating system
- Experience as technical specialist in design and architecture
- Experience in consulting, design and implementation of serverless distributed solutions
- Experience in software development with object oriented language
- Experience in data and machine learning engineering and cloud native technologies
- Experience building complex highly-scalable systems that involve predictive models or applications of machine learning
PREFERRED QUALIFICATIONS - Knowledge of AWS services including compute, storage, networking, security, databases, machine learning, and serverless technologies
- Experience in external or internal customer facing, complex and large scale project management
- Experience in database (eg. SQL, NoSQL, Hadoop, Spark, Kafka, Kinesis)
- Experience with Machine and Deep Learning toolkits such as MXNet, TensorFlow, Caffe and PyTorch
- Experience facilitating discussions with senior leadership regarding technical / architectural trade-offs, best practices, and risk mitigation

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( ) to know more about how we collect, use and transfer the personal data of our candidates.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

Over de vacature

Overview

As a Senior Consultant in EY's Quantitative Advisory Services, you apply quantitative methods to financial risk management for banking and other financial institutions. You'll contribute to model development, validation, and implementation, while exploring topics like AI and ESG integration. You work with cross-functional teams to solve regulatory and risk challenges and help grow EY's risk analytics capabilities. This role offers exposure to high-impact risk projects and a path to further professional development within a global, AI-enabled advisory practice.

Arbeidsvoorwaarden / Benefits

• competitive salary
• pension plan
• holiday allowance and annual bonus
• hybrid working
• mobility budget (lease car or transport)
• 29 vacation days + option to buy extra days

Verantwoordelijkheden

• Develop and validate financial risk, pricing, or AI models for credit, market, and regulatory use
• Support model implementation and governance, including regulatory compliance
• Contribute to risk management transformations and client-oriented solutions
• Build strong client relationships and contribute to business development
• Engage in AI-driven and ESG-related modeling initiatives

Belangrijkste vereisten

• 3+ years of experience in financial services (institution, advisory, or regulation)

• Master's degree in a quantitative field (e.g., econometrics, mathematics, statistics, data science, CS, engineering, physics)

• Experience with data analytics and AI/ML techniques in financial services

• Hands-on experience in development/validation/implementation of risk or AI models

• Programming experience in Python, R, VBA, Java, C++, SQL, Matlab or .NET

• Ability to drive business development for EY market solutions

• Client relationship building

• Strategic thinking and communication

• Team collaboration and cross-functional work

• Python

• R

• SQL

Over de vacature

Overview

As an AI Security Consultant, you will help clients secure AI systems and adopt AI responsibly. You'll work across advisory, assessment, and implementation, collaborating with cross-functional teams to translate risk into concrete actions. You'll apply security frameworks to real environments and contribute to AI-native security delivery. This role combines deep technical insight with strategic mentoring to drive secure AI outcomes at scale.

Arbeidsvoorwaarden / Benefits

• 4x9 workweek
• Hybrid working
• Annual bonus
• Health insurance
• 26 vacation days
• Parental and other special leaves

Verantwoordelijkheden

• Lead client engagements across AI security assessment, advisory, and implementation with growing ownership
• Assess and improve AI system security using frameworks like OWASP LLM Top 10 and MITRE ATLAS; identify gaps and remediation
• Support AI-native security delivery and Cyber.AI deployments with forward-deployed engineers
• Translate security risk to CISO and control requirements to development teams
• Translate regulatory frameworks (DORA, NIS2, EU AI Act) into concrete client requirements and designs
• Advise on securing AI across people, process, and technology, not just technology
• Contribute to methodology, assessment tooling, sector perspectives, and business development including proposals and RFPs

Belangrijkste vereisten

• Approx. 3-6 years of related experience in cybersecurity, technology consulting, security engineering, or similar

• Working understanding of AI/ML systems; knowledge of LLM applications, RAG architectures, and agentic systems

• Solid cybersecurity foundation across frameworks, controls, and risk assessment

• Understanding of securing AI and responsible AI use

• Ability to engage credibly with engineering and MLOps teams

• Strong structuring and communication skills

• Genuine curiosity about AI security and comfort with ambiguity

• Genuine curiosity about AI security

• Comfort with ambiguity

• Strong communication and stakeholder engagement

• Understanding of LLMs, RAG, and agentic AI systems

• Cybersecurity frameworks, controls, risk assessment

• Experience engaging with engineering and MLOps teams