Machine Learning Engineer

Position: Machine Learning Engineer )
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.

We are looking for a motivated and passionate Machine Learning Engineers for our team.

As part of this job, 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

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

Additional Skills Required

Python, Spark, Hadoop, Docker, with an emphasis on good coding practices in a continuous integration context, model evaluation, and experimental design

Test-driven development (prefer py. test/nose), experience with Cloud environments

Proficiency in statistical tools, relational databases, and expertise in programming language like python/SQL is desired.

Good to have

Knowledge of ML frameworks like Scikitlearn, Tensorflow, Keras, etc.

Knowledge of MLflow, Airflow, Kubernetes

Knowledge on any of the cloud-native MLaaS offerings like AWS Sage Maker, Azure

ML, or Google AI platform

Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.

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