Machine Learning Engineer

Tiger Analytics is looking to recruit for a motivated and passionate Machine Learning Engineers for our team.

You will be responsible for:
Providing solutions for the deployment, execution, validation, monitoring, and improvement of data science solutions
Creating Scalable Machine Learning systems that are highly performant
Building reusable production data pipelines for implemented machine learning models
Writing production-quality code and libraries that can be packaged as containers, installed and deployed
Experience and proficiency -
Spark (including spark streaming), Python and SQL
AWS - EMR, Lambdas, S3
Creating data pipelines for ML, specifically sourcing and munging data, as well as preparing features
Experience with Optimization(tuning code and algorithms) and operationalization of models
Requires very little hand-holding in terms of skills and is able to navigate the organization independently
Can work with CI-CD pipelines using Jenkins, Git etc
Knowledge and optionally some experience
Airflow orchestration pipelines
Kafka streaming end points
Good to know
Infra devops including Kubernetes
Bachelor's degree or higher in computer science or related, with 5+ years of work experience
Ability to collaborate with Data Engineers and Data Scientist to build data and model pipelines and help running machine learning tests and experiments
Ability to manage the infrastructure and data pipelines needed to bring ML solution to production
End-to-end understanding of applications being created and maintain scalable machine learning solutions in production
Ability to abstract complexity of production for machine learning using containers
Ability to troubleshoot production machine learning model issues, including recommendations for retrain, revalidate, and improvements
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.
Requirements
Experience and proficiency -
Spark (including spark streaming), Python and SQL
AWS - EMR, Lambdas, S3
Creating data pipelines for ML, specifically sourcing and munging data, as well as preparing features
Experience with Optimization(tuning code and algorithms) and operationalization of models
Requires very little hand-holding in terms of skills and is able to navigate the organization independently
Can work with CI-CD pipelines using Jenkins, Git etc
Knowledge and optionally some experience
Airflow orchestration pipelines
Kafka streaming end points
Good to know
Infra devops including Kubernetes
Bachelor's degree or higher in computer science or related, with 5+ years of work experience
Ability to collaborate with Data Engineers and Data Scientist to build data and model pipelines and help running machine learning tests and experiments
Ability to manage the infrastructure and data pipelines needed to bring ML solution to production
End-to-end understanding of applications being created and maintain scalable machine learning solutions in production
Ability to abstract complexity of production for machine learning using containers
Ability to troubleshoot production machine learning model issues, including recommendations for retrain, revalidate, and improvements
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.
Benefits
Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our consultants bring deep expertise in Data Science, Machine Learning, and AI. Our business value and leadership have been recognized by various market research firms, including Forrester and Gartner.