Company Description

Arηs Group – part of Accenture - is a market leader in the management of complex IT projects and systems. Founded in Luxembourg in 2003, we have grown to encompass 12 entities worldwide, employing over 2,500 employees in Luxembourg, Belgium, Greece, Italy, Portugal and Bulgaria. With our focus on getting things done, we help our clients achieve their goals with best-of-breed solutions, superior execution and exceptional services. We offer bespoke software development, data science, infrastructure, digital trust and mobile development to government institutions at national and European level, telecom providers, and financial institutions, among others. Our bold company culture is built around working hard and playing hard, with a flat and agile structure that lends itself to efficiency and employee empowerment. We value our diverse workplace of close-knit teams and provide a place where everyone can be supported to learn and evolve.

Job Description

ARHS Group – part of Accenture – is looking for an experienced AI Architect specializing in MLOps & DevOps, responsible for designing and implementing the infrastructure, frameworks, and processes required to deploy, monitor, scale, and maintain machine learning models in production environments.

This role combines expertise in both AI/ML model development and DevOps practices to streamline the end-to-end machine learning lifecycle. As AI Architect, you will ensure that AI models are not only effective and accurate but also scalable, efficient, and reliable when deployed in real-world applications. This role requires advanced knowledge of Continuous Integration/Continuous Delivery pipelines, containerization, orchestration tools, and model versioning to enable seamless integration and operationalization of AI systems.

You will work closely with data scientists, software engineers, IT operations, and business teams to design and implement the best practices for managing and optimizing AI/ML deployments across diverse environments (cloud, on-prem, hybrid).

Role & responsibilities

• Designing and building scalable, reliable, and secure MLOps platforms to automate the deployment, monitoring, and maintenance of AI models in production.
• Optimizing AI/ML systems for performance, latency, and cost efficiency at scale.
• Collaborating with data science teams to containerize machine learning models and deploying them in scalable environments such as cloud or hybrid systems.
• Automating model training, validation, and deployment processes to increase the velocity and reliability of model updates and ensuring models can be deployed without manual intervention.
• Monitoring the entire lifecycle of deployed models, identifying bottlenecks, troubleshooting issues, and scaling solutions as needed.
• Leading the design and implementation of cloud-based (AWS, Azure) or on prem AI infrastructure to support large-scale machine learning operations.
• Architecting and maintaining AI/ML services on cloud platforms, ensuring they align with security, governance, and compliance requirements.
• Staying current with the latest trends, research, and technologies in MLOps, DevOps, AI, and cloud computing to continuously improve the efficiency and scalability of AI systems.
• Contributing to the development and optimization of AI/ML frameworks and tools used in production systems.

Qualifications

Technical Expertise

• Expertise in MLOps tools and platforms (e.g., MLflow, Kubeflow, TFX, Metaflow) for model management and orchestration.
• Advanced knowledge of containerization (Docker) and orchestration technologies (Kubernetes) for deploying and scaling machine learning models in production.
• Strong experience with cloud platforms (AWS, Azure) and using cloud-native tools (e.g., AWS SageMaker) for model deployment and infrastructure management.
• Experience with monitoring and alerting systems for tracking AI model performance (e.g., Prometheus, Grafana, ELK Stack).
• Familiarity with machine learning frameworks and libraries (TensorFlow, PyTorch, scikit-learn, etc.) as well as model performance evaluation techniques.
• Understanding of data security, model confidentiality, and compliance requirements (GDPR, HIPAA, etc.) in the deployment of AI/ML systems.
• Experience in implementing robust access control, logging, and auditing mechanisms for AI systems in production environments.

Additional Information

Don’t hesitate! Join our team

What you’ll get:

An informal hierarchy and work environment:

Our open, flat structure supports a strong focus on communication and collaboration, enabling to respond quickly to market changes and customer requests.

An attractive salary package:

With an attractive salary and benefits package – including advantageous fringe benefits – you’ll be paid for what you love to do.

A strong corporate culture:

You’ll join a dynamic team of smart and ambitious people. From the way we hire to the way we relate to our clients – our values form the foundation of the way we work.

Learning & development opportunities:

We constantly invest in our people and are committed to providing individual development opportunities to help you continue to grow and stay happy and satisfied at work.

Exciting projects:

You’ll take ownership of various projects for both public and private clients: calling for creativity and innovation, at the cutting-edge of technology.

A rock-solid company:

With more than 200 customers, and 15% turnover growth in FY2022, you’ll join a business with a sustainable and growth-oriented plan.

But let’s talk about it face to face!

You have the qualities listed above? Please, send us your CV, which will be processed in full confidentiality.

You don’t have all the above requirements but own a great part of them? You can send us your CV too because we will give you the opportunity to grow with us.