Our client is a global IT consulting company specializing in software development, agile transformation, and digital innovation. With a strong focus on delivering high-quality solutions, they empower businesses to achieve technological excellence through cutting-edge technologies and methodologies. Known for fostering a culture of continuous learning and collaboration, they partner with leading organizations to drive their digital transformation journeys. The company operates across multiple industries, offering expertise in areas such as cloud computing, data engineering, and DevOps practices.
responsibilities :
Develop and deploy machine learning models using MLflow and Seldon Deploy, ensuring robust and scalable ML pipelines
Manage infrastructure using Kubernetes and Infrastructure as Code (IaC) with Terraform, optimizing cloud solutions (GCP preferred)
Collaborate with cross-functional teams to align technical solutions with business goals and ensure commercial impact
Automate workflows and CI/CD pipelines using GitHub Actions, while managing data storage and processing with Snowflake
Apply Python (with DBT) for data transformation and integration, ensuring the effective deployment of ML solutions
requirements-expected :
Strong experience with MLflow for machine learning lifecycle management
Expertise in Kubernetes for container orchestration and Terraform for Infrastructure as Code (IaC)
Experience with Seldon Deploy for model serving and deployment
Proficiency in Python, with experience using DBT for data transformation
Familiarity with Snowflake for data warehousing and GitHub Actions for CI/CD
Strong commercial mindset, with the ability to connect technical work to business outcomes
Enthusiastic, open to asking questions, and a team player with excellent communication skills
