Machine Learning Engineer

Summary

Join Tiger Analytics as we continue to build the best global analytics consulting team in the world. We are looking for top-notch talent to provide solutions for data science deployment, create scalable machine learning systems, and collaborate with cross-functional teams.

Requirements

• Bachelor's degree or higher in computer science or related, with 6+ 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
• Ability to manage the infrastructure and data pipelines needed to bring ML solutions to production
• End-to-end understanding of applications being created
• Ability to maintain scalable machine learning solutions in production
• Ability to abstract the complexity of production for machine learning using containers
• Ability to troubleshoot production machine learning model issues, including recommendations for to retrain and revalidate
• Experience with Big Data Projects using multiple types of structured and unstructured data
• Ability to work with a global team, playing a key role in communicating problem context to the remote teams
• Excellent communication and teamwork skills

Responsibilities

• Provide solutions for the deployment, execution, validation, monitoring, and improvement of data science solutions
• Create Scalable Machine Learning systems that are highly performant
• Build reusable production data pipelines for implemented machine learning models
• Write production-quality code and libraries that can be packaged as containers, installed and deployed

Preferred Qualifications

• 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
• Knowledge of MLflow, Airflow, and Kubernetes
• Experience with Cloud environments and knowledge of offerings such as AWS SageMaker OR Azure ML
• Proficiency in statistical tools, relational databases, and expertise in programming languages (Python/SQL)