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Machine Learning Engineer

Remote:

Full Remote

Contract:

Full time

Experience:

Mid-level (2-5 years)

Work from:

United States

Offer summary

Qualifications:

Bachelor's degree in computer science or related field, 6+ years of work experience, Experience with Python, Spark, Hadoop, Docker, Knowledge of ML frameworks like Scikit-learn and Tensorflow, Proficiency in statistical tools and relational databases.

Key responsabilities:

Deploy, execute, validate and monitor data science solutions
Create scalable machine learning systems
Build reusable production data pipelines
Write production-quality code for deployment
Collaborate with teams to drive strategy and communicate results

Tiger Analytics XLarge https://www.tigeranalytics.com/

1001 - 5000 Employees

See more Tiger Analytics offers

Job 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. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner.

We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world. 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

You will collaborate with cross-functional teams and business partners and will have the opportunity to drive current and future strategy by leveraging your analytical skills as you ensure business value and communicate the results.

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

Additional Skills Required

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)

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.

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