Job Description:
AI Engineer – Develop Advanced AI and ML Systems
The AI Engineer plays a crucial role in transforming artificial intelligence from concept to production. You will be responsible for building robust, scalable AI systems that directly support our consultancy’s core products, tools, and client-facing solutions.
In this position, you’ll bridge the gap between research and application. You will take models built by data scientists and researchers and turn them into real-world, deployable software. Your work will focus on integrating machine learning and AI components into digital media tools that support optimization, personalization, targeting, and content generation.
You’ll work across the full AI development lifecycle. This includes designing pipelines, preparing infrastructure for training and testing, and deploying models into scalable environments. You’ll also monitor system performance, manage version control, and ensure continuous integration and delivery of AI services.
Collaboration will be a core part of your role. You’ll partner with data teams, DevOps engineers, and product managers to align technical systems with strategic business goals. Together, you’ll bring AI features into platforms that drive measurable results.
Additionally, you’ll implement APIs and automation layers to connect AI outputs with applications and user-facing tools. You’ll help ensure that models work reliably in production, adapting systems as data changes and user demands evolve.
Your work will also involve experimentation. You’ll be expected to test new architectures, measure performance against KPIs, and iterate quickly. Balancing engineering best practices with rapid prototyping is key in this dynamic role.
Strong knowledge of Python, cloud services (like AWS, GCP, or Azure), and frameworks such as TensorFlow, PyTorch, or MLflow is essential. Experience with MLOps, containerization tools (e.g., Docker, Kubernetes), and model monitoring platforms is highly valuable.
The AI Engineer is a builder — someone who brings AI models to life at scale. Your work ensures that advanced models are not only accurate but also stable, secure, and production-ready.
This position is central to our AI delivery pipeline. Your ability to operationalize innovation will help our clients benefit from powerful, reliable, and intelligent systems.
Find our other roles here. Find other details regarding digital and AI roles.
Responsibilities:
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Develop and deploy machine learning models in production environments.
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Translate research code and prototypes into production-grade systems.
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Build and maintain model training, testing, and inference pipelines.
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Work with data scientists to define architecture and integration needs.
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Monitor deployed models for performance, drift, and reliability.
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Integrate AI features into customer-facing applications and tools.
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Collaborate with DevOps and software engineers on cloud infrastructure.
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Document workflows and processes for reproducibility and collaboration.
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Support CI/CD practices and automation around AI deployments.
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Stay updated on the latest in AI tools, libraries, and infrastructure best practices.
Preferred Qualifications:
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3+ years of experience as an AI Engineer or ML Engineer.
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Proficient in Python and ML frameworks like PyTorch, TensorFlow, or XGBoost.
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Experience with MLOps tools and cloud platforms (AWS, GCP, Azure).
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Knowledge of software engineering practices including testing and version control.
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Understanding of data pipelines, APIs, and model lifecycle management.
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Experience deploying AI solutions at scale in production settings.
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Strong problem-solving skills and the ability to debug complex systems.
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Experience in media, martech, or content automation is a plus.
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Degree in Computer Science, Engineering, or related technical discipline.
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Passion for building intelligent, automated systems with real business impact.
