Senior Machine Learning Engineer

Who you are

You have a Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field, and you bring at least 5 years of experience in machine learning engineering. You are skilled in designing and implementing robust data pipelines for training machine learning models, and you have a deep understanding of model deployment strategies. Your expertise in Python and familiarity with cloud services like AWS enable you to create scalable solutions that meet production demands.

You are proficient in developing APIs and microservices that facilitate communication between machine learning models and other software modules. Your experience with Docker and orchestration tools allows you to optimize deployment processes effectively. You are a critical thinker who enjoys collaborating with cross-functional teams to identify bottlenecks and implement solutions that enhance workflow efficiency.

You have a strong commitment to implementing best practices for managing and deploying machine learning models, ensuring reliability, scalability, and security in production environments. Your ability to monitor and log model performance, data quality, and system health in real-time is a key asset that you bring to the team. You are also adept at implementing cost-saving strategies to minimize infrastructure expenses while maximizing performance.

Desirable

Experience with additional cloud platforms or tools such as Azure or Google Cloud Platform would be a plus. Familiarity with machine learning frameworks like TensorFlow or PyTorch can enhance your contributions to the team. You are encouraged to apply even if your experience doesn't match every requirement, as we value diverse backgrounds and perspectives.

What you'll do

As a Senior Machine Learning Engineer at SageSure, you will play a crucial role in optimizing orchestration processes and ensuring fast and efficient model deployment and delivery. You will design and implement robust, scalable, and efficient data pipelines for training machine learning models, ensuring that they are seamlessly integrated into production environments. Your work will involve developing prediction pipelines and creating APIs and microservices to facilitate communication between machine learning models and other software modules.

You will be responsible for designing, building, and managing model deployment strategies that ensure reliability, scalability, and security in production environments. Implementing monitoring and logging solutions to track model performance, data quality, and system health in real-time will be a key part of your role. You will also optimize orchestration processes to ensure efficient deployment and management of ML models, collaborating with cross-functional teams to identify bottlenecks and implement solutions to improve workflow efficiency.

What we offer

At SageSure, we offer a dynamic work environment where you can thrive and grow. You will be part of a profitable, growing company that values innovation and encourages you to bring your authentic self to work. Our culture nurtures critical thinkers who are empowered to run toward problems and engineer solutions. We invest in the technology, talent, and tools that position us to succeed in demanding markets, and we are committed to providing our employees with the support they need to excel in their roles.