We are a dynamic team focused on building scalable and secure machine learning solutions in cloud environments. Our projects involve designing and deploying end-to-end MLOps pipelines, containerized workloads, and automated CI/CD processes using Azure services. We leverage cutting-edge technologies such as Azure ML, Kubernetes, Docker, MLflow, and Terraform to deliver robust, production-ready AI solutions.
What makes you a great fit?
Key technologies
Azure Machine Learning | Azure Kubernetes Service (AKS) | Azure DevOps | Docker | Kubernetes | MLflow | Terraform | Python | CI/CD | IaC
- Proficiency in Python 3+ years of experience in developing ML pipelines and integrating with frameworks (PyTorch, TensorFlow).
- Hands-on experience with Azure services including Azure ML, AKS, and Azure DevOps for end-to-end MLOps workflows.
- Strong knowledge of containerization and orchestration using Docker and Kubernetes for scalable, fault-tolerant deployments.
- Familiarity with MLOps practices including MLflow for experiment tracking, model registry, and artifact management.
- Experience with Infrastructure as Code (IaC) using Terraform, Bicep, or ARM templates for automated and secure cloud environments.
Nice to have
- Experience with Kubeflow or Vertex AI for advanced ML orchestration.
- Background in Python-based ML frameworks (PyTorch, Scikit-learn, TensorFlow).
- Knowledge of data privacy, compliance, and responsible AI principles.
Soft skills
- Analytical Thinking
Ability to interpret data, identify trends, and provide actionable insights to drive business decisions. - Problem-Solving Skills
Proactively identify and resolve issues related to BI systems, ensuring smooth operations and data accuracy. - Effective Communication
Ability to explain technical concepts to non-technical stakeholders clearly and concisely, fostering understanding and collaboration. - Attention to Detail
Meticulous in data validation, report generation, and ensuring data quality across BI platforms. - Team Collaboration
Strong interpersonal skills to work effectively in cross-functional teams, coordinating with IT, business analysts, and other stakeholders. - Adaptability and Continuous Learning
Open to learning new tools and technologies in the rapidly evolving BI landscape and adjusting to changing business needs.
What will you do?
- Design and implement end-to-end MLOps pipelines in Azure using services like Azure ML, AKS, ACR, and Azure Data Lake.
- Containerize and orchestrate machine learning workloads using Docker and Kubernetes for scalable, fault-tolerant deployment.
- Automate training, validation, and deployment of models through CI/CD pipelines integrated with Git and workflow orchestration tools (Airflow, MLflow, Kubeflow).
- Manage model versioning, lineage, and registry using Azure ML Model Registry or equivalent.
- Implement monitoring and alerting for model drift, data quality, and inference performance.
- Ensure infrastructure as code (IaC) using tools like Terraform, Bicep, or ARM templates.
- Apply security and compliance best practices across model storage, API endpoints, and data access.
Our benefits
Your journey with us starts here:
1. Initial Screening: If you meet our requirements, our recruiter will reach out to you for a chat about your motivations and expectations. Get ready to share your passion!
2. Technical Interview: Next, you'll be invited to showcase your skills in an interview with one of our technical experts or team members. This is your chance to shine and demonstrate your expertise.
3. Final Interview: Finally, you'll have the opportunity to meet your future Team Lead. This is the perfect moment to learn more about the role, the team, and to ask any questions you might have.