Job Description
Join a leading data-driven enterprise working at the forefront of retail innovation. As a Machine Learning Engineer, you’ll design, scale, and deploy production-grade ML solutions that solve complex business challenges and deliver tangible impact across high-traffic platforms.
This is an opportunity to work in a modern, cloud-native environment alongside top-tier Data Scientists and Engineers, using the latest in GCP technologies and orchestration tools.
What You’ll Do:
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Build, deploy, and maintain scalable ML pipelines using Google Cloud technologies.
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Develop robust data models, APIs, and predictive solutions to solve business-critical problems.
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Collaborate closely with cross-functional teams in an agile setting to deliver high-impact data products.
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Champion engineering best practices, testing frameworks, and architectural reviews to ensure quality and reliability.
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Drive innovation through continuous learning and the adoption of new technologies and frameworks.
What You’ll Bring:
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Bachelor’s degree or higher in Computer Science, Engineering, or a related field.
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3+ years of experience in commercial software development.
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2+ years of hands-on experience with Python, SQL, and Linux environments.
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Experience with ML orchestration tools such as Vertex AI Pipelines, Kubeflow, Argo, or Airflow.
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Proficiency with Docker or Kubernetes for containerized deployments.
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Familiarity with modern ML methods (e.g., GNNs, LLMs) and MLOps best practices.
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Exposure to microservices architecture and tools like dbt core is a plus.
Why Join?
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Be part of high-impact projects that blend data science and software engineering.
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Work in a flexible, inclusive, and innovation-focused environment.
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Access cutting-edge tools and cloud technologies.
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Grow your career with continuous learning and hands-on experience in solving real-world problems.