Machine Learning Engineer (Canada)

Tiger Analytics; Toronto; On-site; CAD 80,000 - 120,000; Full time

Job summary

An innovative analytics consulting firm is seeking a passionate Machine Learning Engineer to join their dynamic team. In this role, you will be at the forefront of deploying and enhancing data science solutions for Fortune 100 companies. You will create scalable machine learning systems and build production data pipelines, ensuring high performance and reliability. This is a unique opportunity to thrive in a fast-paced, entrepreneurial environment where your contributions significantly impact the company's growth and success. If you are driven by challenges and eager to make a difference, this position is perfect for you.

Benefits

Career development opportunities

Entrepreneurial environment

High degree of individual responsibility

Qualifications

• 5+ years of experience in machine learning and data science.
• Strong coding skills in Python and experience with Docker.

Responsibilities

• Deploy and monitor data science solutions and improve their performance.
• Build reusable production data pipelines for machine learning models.

Skills

Machine Learning

Data Science

Python

Communication Skills

Teamwork

Problem Solving

Education

Bachelor's degree in Computer Science

Master's degree in related field

Tools

Docker

Spark

Hadoop

ML frameworks (Scikit-learn, TensorFlow, Keras)

Cloud environments

MLflow

Airflow

Kubernetes

Job 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 Engineer 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.

Minimum Requirements:

• Bachelor's degree or higher in computer science or related field, with 5+ 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 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 languages like Python/SQL is desired.

Good to have:

• Knowledge of ML frameworks like Scikit-learn, TensorFlow, Keras, etc.
• Knowledge of MLflow, Airflow, Kubernetes.
• Knowledge of any of the cloud-native MLaaS offerings like AWS SageMaker, AzureML, 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.