Machine Learning Architect – AI Solutions

About the role

The Machine Learning Architect will design and develop scalable AI‑driven solutions that tackle complex business challenges and improve decision‑making processes. You will work with large, intricate data sets and lead the end‑to‑end creation of production‑grade ML pipelines.

Key responsibilities

• Develop, train, and optimise machine learning, neural network and agentic models using state‑of‑the‑art algorithms.
• Build end‑to‑end ML pipelines covering data ingestion, transformation, model training, validation and deployment.
• Automate model training, testing and deployment through CI/CD pipelines and MLOps tools such as MLflow and Kubeflow.
• Collaborate with cross‑functional teams to integrate models into applications via API development (FastAPI, Flask).
• Fine‑tune large language models (SLMs/LLMs) and construct complex AI architectures.

Required profile

• 3‑7 years of experience building production‑grade, scalable AI systems.
• Strong expertise in supervised/unsupervised learning, deep learning, NLP, computer vision or generative AI.
• Solid understanding of ML system architecture, model serving and performance optimisation for real‑time or batch inference.
• Bachelor’s degree in Computer Science, Engineering or a related field (Master’s/PhD preferred).

Required skills

• Generative AI
• SLMs / LLMs
• ML system architecture
• MLflow
• Agentic models
• Model serving API development (FastAPI, Flask)
• CI/CD pipelines
• Batch inference
• Kubeflow
• Machine Learning, Unsupervised Learning, Deep Learning
• MLOps
• Docker
• Kubernetes
• AWS
• Azure