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Urgent! Valuebound - MLOps Engineer - Data Modeling Job | Valuebound

Valuebound MLOps Engineer Data Modeling



Job description

<p>Responsibilities : </p><p><br/></p><p>- Manage Data : Extract, clean, and structure both structured and unstructured data.<br/><br/>- Coordinate Pipelines : Utilize tools such as Airflow, Step Functions, or Azure Data Factory to orchestrate data workflows.<br/><br/>- Deploy Models : Develop, fine-tune, and deploy models using platforms like SageMaker, Azure ML, or Vertex AI.<br/><br/>- Scale Solutions : Leverage Spark or Databricks to handle large-scale data processing tasks.<br/><br/>- Automate Processes : Implement automation using tools like Docker, Kubernetes, CI/CD pipelines, MLFlow, Seldon, and Kubeflow.<br/><br/>- Collaborate Effectively : Work alongside engineers, architects, and business stakeholders to address and resolve real-world problems efficiently.<br/><br/>Requirements : </p><p><br/></p><p>- 3+ years of hands-on experience in MLOps (4-5 years of overall software development experience).<br/><br/>- Extensive experience with at least one major cloud provider (AWS, Azure, or GCP).<br/><br/>- Proficiency in using Databricks, Spark, Python, SQL, TensorFlow, PyTorch, and Scikit-learn.<br/><br/>- Expertise in debugging Kubernetes and creating efficient Dockerfiles.<br/><br/>- Experience in prototyping with open-source tools and scaling solutions effectively.<br/><br/>- Strong analytical skills, humility, and a proactive approach to problem-solving.<br/><br/>- Experience with SageMaker, Azure ML, or Vertex AI in a production environment.<br/><br/>- Commitment to writing clean code, creating clear documentation, and maintaining concise pull request<br/></p> (ref:hirist.tech)


Required Skill Profession

Computer Occupations



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