About Brillio
Brillio LLC is a fast-growing, pure-play Digital Transformation Solutions and Services company backed by Bain Capital private equity. Founded in 2014 and headquartered in Silicon Valley, Brillio is focused on delivering design-led solutions for our customers. We are not an IT Services company trying to pivot and support the “next big thing.” As a digitally native company, everything we have done and will continue to do, will have this laser focus. Brillio delivers disruptive digital solutions across capabilities such as Design Thinking, Product Engineering, Data Analytics, Digital Front Office, and Digital Infrastructure. Our core values of Customer success, We Care, Entrepreneurial (mind set) and Excellence - drive everything that we do, from the very first day.
Brillio Romania
Brillio Romania is a dynamic and rapidly growing company with over 160 employees and offices in Cluj, Oradea, and Bucharest. With its fast-paced growth, the company has consistently demonstrated an unwavering commitment to client satisfaction.
At Brillio Romania, we know our success comes from the innovative contributions and brilliant work of our people. So, we make fostering a positive work environment our top priority. Employees at Brillio Romania not only thrive, but they also have the chance to build long and fulfilling careers, fostering a sense of stability and dedication that ultimately benefits both the company and our valued clients.
Role: MLOps Engineer - Based in Romania (Fully Remote)
Key Responsibilities:
- Setup Databricks platform as MLOps platform leveraging native Databricks capabilities like MLflow, unity calaog
- ML Model Deployment & Management: Lead the deployment and monitoring of machine learning models in production environments, ensuring scalability, reliability, and performance.
- End-to-End Pipeline Automation: Design and implement automated data and model pipelines using tools like Azure Machine Learning, Databricks, and other orchestration platforms.
- Model Monitoring and Maintenance: Setup frameworks for establishing systems for tracking model performance, addressing drift, and ensuring ongoing optimization of ML models.
- Collaboration with Data Engineers and Scientists: Work closely with data scientists to transition models from development to production while collaborating with data engineers to ensure data pipeline integrity.
- Cloud Infrastructure: Design scalable cloud architectures for ML workloads using Azure, leveraging services like Azure Machine Learning, Azure Databricks, Azure Synapse, and Azure Data Lake.
- Security and Compliance: Ensure that the ML systems comply with organizational standards for security, data privacy, and governance.
- Continuous Improvement: Focus on enhancing operational efficiency, reducing manual intervention, and improving deployment processes through automation and advanced MLOps practices.
Key Skills:
- Databricks: Expertise in using Databricks for data engineering, model training, and real-time analytics.
- MLOps Frameworks: Proficiency in tools and frameworks such as MLflow, Kubeflow, or TensorFlow Extended (TFX) for managing the machine learning lifecycle.
- Version Control & CI/CD: Experience with version control systems (e.g., Git) and implementing CI/CD pipelines for automated model deployment.
- Containerization: Knowledge of Docker and Kubernetes for model containerization and orchestration.
- Monitoring & Logging: Implement monitoring and logging frameworks using tools like Azure Monitor, Datadog, or Prometheus to ensure model performance and traceability.
- Data Engineering: Strong experience with big data processing frameworks such as Apache Spark, Apache Kafka, and other ETL tools.
Take the next step with Brillio. Accelerate What Matters. Now. Be a Catalyst for Tomorrow, Be a Brillian!
