Tiger Analytics

Delivers Data and AI transformation

Machine Learning Engineer

Applied Machine LearningConfirmed live in the last 24 hours

Full-timeToronto, ON, CanadaNo salary listedIn-person

About the Job

Requirements

A bachelor's degree or higher in computer science or a related field, with at least five years of work experience.
Collaborate with data engineers and data scientists to build data and model pipelines and help run machine-learning tests and experiments.
Manage the infrastructure and data pipelines needed to bring machine-learning solutions to production.
Understand applications end to end and maintain scalable machine-learning solutions in production.
Abstract production complexity for machine learning using containers.
Troubleshoot production machine-learning model issues and recommend retraining, revalidation, and improvements.
Have experience with big data projects using multiple types of structured and unstructured data.
Work with a global team and communicate problem context to remote teams.
Use Python, Spark, Hadoop, and Docker, with good coding practices in a continuous-integration context, model evaluation, and experimental design.
Use test-driven development, preferably Pytest or nose, and have experience with cloud environments.

Responsibilities

Provide solutions for the deployment, execution, validation, monitoring, and improvement of data-science solutions.
Create scalable, high-performance machine-learning systems.
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.

Desired Qualifications

Have proficiency in statistical tools and relational databases, and expertise in a programming language such as Python or SQL.
Know machine-learning frameworks such as scikit-learn, TensorFlow, or Keras.
Know MLflow, Airflow, or Kubernetes.
Know cloud-native machine-learning-as-a-service offerings such as AWS SageMaker, Azure Machine Learning, or Google AI Platform.

Machine Learning Engineer (Canada)

Tiger Analytics Inc. · Toronto, Canada · Full-time · Posted 2022-09-12

Workplace: on_site

Department: MLE

Description

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

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 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 SageMaker, AzureML, or Google AI platform

Benefits

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.

Apply

Apply at Tiger Analytics Inc.

About the Company

Tiger Analytics

Delivers Data and AI transformation

Tiger Analytics helps large organizations plan and execute Data and AI–led transformations at scale. It works with clients to translate business needs into data and AI initiatives, using an approach that combines business value mapping, agile operating models, and a platforms-based architecture, backed by partnerships with major hyperscalers. The company designs and delivers end-to-end data and AI solutions—from strategy and data engineering to model development and deployment—so that AI can be applied to tough, real-world problems. Unlike firms that rely mainly on standard playbooks, Tiger Analytics builds custom approaches and accelerators to suit each client’s value chain and operating model. With a global team of 5000+ technologists and consultants, the goal is to enable measurable value and practical outcomes through data and AI programs that work at enterprise scale.

Company size: 1,001-5,000
Company stage: Not listed
Total funding: Not listed
Headquarters: San Jose, CA
Founded: 2010

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