We are seeking a talented and motivated ML Engineer with a strong foundation in machine learning and a proven track record in deploying and maintaining models in production environments. As an ML Engineer (CONOO801), you will play a crucial role in our data-driven initiatives, working closely with cross-functional teams to implement and optimize machine learning solutions. The ideal candidate possesses expertise in Docker, Kubernetes, SQL, and Python, demonstrating proficiency in deploying and scaling machine learning models efficiently.
Key skils
Machine Learning Development: Design, develop, and implement machine learning models to address complex business challenges.
Model Deployment and Scaling: Utilize Docker and Kubernetes to deploy and scale machine learning models in production environments, ensuring reliability and scalability.
Data Management: Proficiently manage and query data using SQL, ensuring data quality and suitability for training and testing machine learning models.
Algorithm Optimization: Fine-tune machine learning algorithms for optimal performance and accuracy, considering factors such as speed, scalability, and resource efficiency.
Codebase Maintenance: Collaborate with software engineering teams to integrate machine learning solutions into the existing codebase, ensuring seamless deployment and compatibility.
Monitoring and Maintenance: Implement systems for monitoring model performance, and conduct regular maintenance to address any issues or improvements required.
Collaboration: Work closely with data scientists, software engineers, and business analysts to understand project requirements and contribute to the overall success of data-driven initiatives.
1. Flexibility:
2. Increased Productivity
3. Cost Savings:
4. Access to a Global Talent Pool:
5. Improved Work-Life Integration:
6. Health and Well-being:
7. Environmental Impact:
8. Increased Autonomy: