MLOps Engineer

Job not on LinkedIn

February 8

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Logo of Tiger Analytics

Tiger Analytics

Artificial Intelligence • B2B • Consulting

Tiger Analytics is a leading AI and analytics consulting firm that specializes in leveraging data science and machine learning to provide strategic business insights across various industries. They offer services in data strategy, AI engineering, and business intelligence to enable data-driven decision-making and digital transformation for their clients. Tiger Analytics collaborates with top technology partners like Microsoft, Google Cloud, and AWS to deliver cutting-edge solutions. They serve a diverse range of sectors including consumer packaged goods, healthcare, and finance, helping businesses operationalize insights and differentiate with AI and machine learning technologies.

1001 - 5000 employees

Founded 2011

🤖 Artificial Intelligence

🤝 B2B

📋 Description

• Tiger Analytics is looking for experienced Machine Learning Engineers to join our fast-growing advanced analytics consulting firm. • Our employees bring deep expertise in Machine Learning, Data Science, and AI. • We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. • You will be responsible for: • ML Engineer with 5-7 years of IT experience. • Pipeline Training Models, Building, Deployment, Testing, and Monitoring using AWS SageMaker, AWS CFT, AWS CodePipeline, Lambda, etc. • Develop Airflow DAGs to run training and scoring pipelines • Develop a Testing framework with Pytest • Implement monitoring solution with homebrew solution using Lambda and Dash • Develop Data Quality solutions potentially leveraging Great Expectations.

🎯 Requirements

• Bachelor's degree or higher in computer science or related, with 5+ years of work experience • Ability to collaborate with Data Engineers and Data Scientists to build data and model pipelines and help run machine learning tests and experiments • Experience in AWS - SageMaker (ProcessingJobs, TrainingModels, EndPoints) • Experience in Lambda CloudFormation or Terraform Apache Airflow, Astronomer Docker • Knowledge of traditional ML Models. • Python, Spark, Hadoop, and Docker with an emphasis on good coding practices in a continuous integration context, model evaluation, and experimental design • Knowledge of ML frameworks like Scikitlearn, Tensorflow, and Keras. • Experience in Pandas, sklearn, Numpy, Scipy • Knowledge of Database/Data Engineering. • Experience with Oracle, Spark, Hadoop, Athena, API, FastAPI, Flask, ReST • Knowledge of MLflow, Airflow, and Kubernetes • Experience with Cloud environments and knowledge of AWS Services, Service Catalog, SNS, SES

🏖️ Benefits

• This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.

Apply Now

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