Posted:1 week ago|
Platform:
Work from Office
Full Time
Role & responsibilities Design, develop, and optimize scalable ML pipelines using Python and modern ML engineering tools. Implement feature stores, model versioning, and model serving using tools like Feast , Kubeflow , and MLflow . Work closely with data scientists to productize machine learning models in production environments. Write and maintain Dockerfiles and Kubernetes YAML configurations to containerize and deploy models and services. Apply performance tuning and optimization techniques to improve ML pipeline efficiency. Work in Big Data environments and integrate with data platforms when required. Collaborate with cross-functional teams including data engineering, DevOps, and product teams to deliver ML solutions. Maintain documentation, ensure version control, and follow best practices for reproducibility and model governance. Preferred candidate profile 5+ years of experience in Python programming with focus on performance tuning and optimization. Proficiency in NumPy , Pandas , and data frame operations. Hands-on experience with Feast , Kubeflow , and MLflow . Solid understanding of Docker and Kubernetes ; ability to write and manage YAML configurations. Working knowledge of Big Data environments (Spark, Hadoop, etc.) is a plus. Strong analytical and problem-solving skills with meticulous attention to detail. Excellent communication and interpersonal skills; ability to thrive in a fast-paced and collaborative environment. Solid understanding of machine learning and data science fundamentals.
Winjit Technologies
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