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As a Backend Engineer on our ML Platform team, you’ll play a crucial role in architecting and building our cutting-edge machine learning platform to support the end-to-end machine learning lifecycle. You will drive business-wide ML projects from an engineering perspective, leveraging cloud-native technologies to empower our data scientists and engineers.
In this role you'llDesign and develop an internal ML platform to support data scientists in their research and development efforts.
Implement cloud-native microservice architecture running on Kubernetes, leveraging infrastructure-as-code to automate the deployment and management of machine learning models.
Drive the end-to-end machine learning lifecycle, from training and testing to deployment and monitoring in real-time or near real-time environments.
Evaluate and select appropriate tools and technologies based on workload characteristics and performance requirements.
Collaborate with cross-functional teams to manage projects with various stakeholders, ensuring alignment with business goals.
4+ years of experience in software engineering, with a strong track record of delivering high-scale, production-grade projects
Proficiency in Python programming skills
Experience working with relational and NoSQL databases, as well as cloud platforms (AWS, Azure, GCP)
Strong problem-solving skills, attention to detail, and ability to thrive in a fast-paced, collaborative environment
Experience with training, testing, deployment, and monitoring real-time (or near real-time) machine learning models in production is a plus
Bachelor's or Master's degree in Computer Science, Engineering, Statistics, or related field
Ability to work in an office environment a minimum of 3 days a week
Enthusiasm about learning and adapting to the exciting world of AI – a commitment to exploring this field is a fundamental part of our culture
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