Senior AI Software engineer

We are looking for an experienced and enthusiastic Senior Software Engineer with a specialized focus on Artificial Intelligence and Research & Development (R&D). As our new Senior AI Software Engineer, you will be responsible for designing and implementing advanced AI solutions within our organization, bridging the gap between theoretical research and production-ready software. You will lead the development of intelligent systems, define the architecture for scalable AI models, and support the broader engineering team in integrating machine learning capabilities into our core products.

Nature of Duties

AI Solution Development: Responsible for providing intelligent solutions to manufacturing and business problems using machine learning, deep learning, and generative AI methodologies.

R&D Innovation: Analyze and prototype new AI technologies and frameworks to solve complex challenges, staying at the forefront of industry trends.

Infrastructure for AI: Manage and optimize the specialized IT infrastructure and GPU-accelerated environments needed to train and deploy large-scale AI models.

Testing & Model Validation: Develop and perform rigorous tests on AI applications, including data validation, model performance benchmarking, and troubleshooting bias or accuracy issues.

CI/CD for Machine Learning (MLOps): Implement and support MLOps pipelines to automate the training, versioning, and deployment of models (Continuous Integration and Continuous Delivery).

Tooling & Standards: Define the best AI frameworks and development tools to be used across the software lifecycle.

Data Security & Ethics: Ensure the integrity, security, and confidentiality of sensitive datasets by applying robust data privacy patterns and ethical AI methods.

Technical Mentorship: Train and provide technical support to users and junior engineers regarding AI features, model interpretability, and newly developed manuals.

Education and Experience

Bachelor's or Master's Degree in Computer Science, Data Science, AI, or a related field.

Advanced experience (4+ years) with AWS is required, specifically using services like SageMaker, EC2 instances, S3, and Lambda to scale AI workloads.

Deep experience with Machine Learning frameworks and LLM orchestration tools.

Experience with Docker and Kubernetes (specifically EKS) for orchestrating containerized AI microservices.

Experience using Terraform or Ansible to manage reproducible research environments.

Expert ability to code and script (Python for exemple).

Experience with high-performance computing (HPC) systems and optimizing IT operations for data-heavy applications.

Excellent communication skills, with the ability to translate complex AI concepts into actionable insights for stakeholders.