Senior AI Engineer

1. AI Solution Development Lead the design and development of innovative machine learning models and algorithms in cross-functional teams to effectively address specific business challenges. Lead the implementation of scalable AI products, ensuring alignment with user requirements and strategic business objectives. Leverage state-of-the-art cloud technologies (e.g., AWS, Azure, Google Cloud) to optimize the industrialization of machine learning models and AI solutions for production deployment.

Provide expert operational support and guidance for machine learning models and algorithms, ensuring their reliability and performance in production environments. Establish and promote advanced data quality assurance processes, including validation checks and proactive data drift detection mechanisms, to ensure data consistency and integrity.

Reference Code:| 878890 | | --- Contact Us +

• Required Master's or Ph.D. degree in Computer Science, Information Technology, Data Science, Artificial Intelligence or a related field or Bachelor's with minimum 8 years experience.
• Proven experience as an AI Engineer, Machine Learning Engineer, or similar role.
• Experience in developing and deploying machine learning models and AI systems.
• Proficiency in programming languages such as Python or R
• Strong knowledge of machine learning frameworks (Tensor Flow, PyTorch, Scikit-learn).
• Experience with natural language processing (NLP), computer vision, or other AI techniques
• Familiarity with big data technologies (Hadoop, Spark) and cloud platforms (AWS, Azure, Google Cloud)
• Strong analytical skills and the ability to work with complex datasets.
• Excellent problem-solving skills with a focus on developing innovative AI solutions.
• Excellent verbal and written communication skills.
• Ability to work collaboratively in a cross-functional team environment.
• Strong organizational skills and the ability to manage multiple AI projects simultaneously.
• Experience with Agile methodologies and tools (Azure Dev Ops, Scrum).

Deep understanding of the Azure ecosystem, specifically Azure AI, Azure Machine Learning, Compute, Storage, Networks and Azure Arc, Containers (registry, runtimes), Events, Functions, Azure Identity tooling

Practical experience with hybrid cloud or edge computing infrastructure (e.g., Azure Stack HCI, Kubernetes on-premises).

Strong proficiency in Python 3 and familiarity with modern AI and automation development stacks and Powershell

Solid understanding of distributed systems, containerization (Docker/Kubernetes), and API design.

Microsoft Teams Bot integrations; understanding of maintaining and publishing bots, React

Azure Databases (CosmosDB, MongoDB, SQL Database, PostgreSQL)

Databricks (Spark/OSP), Log Analytics, Kafka