Consultant

KPMG Delivery Network (KDN) is seeking a highly skilled AI Engineer to join our pioneering team. This role is crucial for developing and deploying advanced AI solutions, leveraging cutting-edge technologies such as Generative AI, Machine Learning, Deep Learning, Neural Networks, and Reinforcement Learning. The AI Engineer will be responsible for designing, coding, and implementing AI components, services, and libraries, working closely with a development team to bring AI products from concept to market.

As an AI Engineer, you will lead the technical execution of AI projects, from initial prototyping to production and market launch, ensuring that AI solutions are built to the highest standards of performance, scalability, and security.

Key responsibilities include:

• Work on design and development of AI models and algorithms using frameworks such as TensorFlow, PyTorch, and Keras.
• Develop and code robust AI components, services, and libraries, ensuring they are scalable, maintainable, and optimized for performance.
• Implement advanced AI techniques, including Generative AI, Reinforcement Learning, and Fine-Tuning, to solve complex business problems.

• Collaborate with AI architects, data scientists, and software engineers to design and build end-to-end AI solutions.
• Provide technical leadership to the development team, guiding them through the design, coding, testing, and deployment of AI models.
• Engage with KPMG member firms and other stakeholders to understand their requirements and translate them into technical solutions.

• Work on all phases of the AI product lifecycle, including prototype development, proof of concept (PoC), minimum viable product (MVP), and full-scale production.
• Work closely with product management and testing teams to ensure that AI products are developed/ launched according to specifications and timelines.
• Drive the continuous improvement of AI products, incorporating user feedback and new technological advancements.

• Deploy AI models and services in cloud environments, primarily using Azure, ensuring scalability, reliability, and security.
• Implement CI/CD pipelines, Docker containers, and Kubernetes for efficient AI model deployment and management.
• Optimize the infrastructure for AI workloads, ensuring cost-effectiveness and high performance.

• Stay up-to-date with the latest developments in AI and machine learning, experimenting with new tools, frameworks, and methodologies.
• Innovate and propose new AI-driven use cases that can bring value to KDN and its member firms.
• Contribute to the development of AI best practices, coding standards, and technical documentation.

• Ensure that all AI solutions comply with KDN’s data privacy, security, and regulatory requirements.
• Implement security best practices in AI model development and deployment, safeguarding sensitive data and intellectual property.

Educational qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
• Advanced certifications in AI/ML, cloud computing, or software engineering are advantageous.

Work experience

• 3+ years of experience in AI, Machine Learning, or related fields, with hands-on experience in developing and deploying AI solutions.
• Proven experience with AI frameworks such as TensorFlow, PyTorch, and Keras, and cloud platforms like Azure.
• Strong background in software development, including experience with Python, Java, or similar programming languages.
• Experience leading AI projects through all phases, from prototype to production.

Skills

• Expertise in designing and coding AI components, services, and libraries.
• Strong understanding of AI/ML algorithms, model optimization, and deployment strategies.
• Proficiency in cloud-based AI development and deployment, particularly with Azure.
• Familiarity with DevOps practices, including CI/CD pipelines, Docker, and Kubernetes.
• Excellent problem-solving skills and the ability to work collaboratively in a cross-functional team environment.
• Strong communication skills, with the ability to translate complex technical concepts into actionable solutions.