Machine Learning Engineer (Canada)

Reposted One Month Ago
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Toronto, ON, CAN
In-Office
50K-120K Annually
Senior level
Big Data • Analytics • Business Intelligence • Big Data Analytics
The Role
The Machine Learning Engineer will create scalable ML systems, build production data pipelines, and ensure robust deployment and monitoring of solutions.
Summary Generated by Built In

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.

Skills Required

  • Bachelor's degree or higher in computer science or related
  • 5+ years of work experience
  • Experience with collaborative work with Data Engineers and Data Scientists
  • End-to-end understanding of applications and maintenance of ML solutions
  • Ability to troubleshoot production ML model issues
  • Experience with Big Data Projects
  • Excellent communication and teamwork skills
  • Proficiency in statistical tools and relational databases

Tiger Analytics Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Tiger Analytics and has not been reviewed or approved by Tiger Analytics.

  • Fair & Transparent Compensation — Feedback suggests pay is viewed as fair and market-aligned for many roles and geographies. Consistent, on-time pay and competitive packages in key markets reinforce a generally positive baseline.
  • Healthcare Strength — Feedback suggests U.S. medical coverage is strong, with administration via a known benefits platform and plan options seen positively. Health insurance is often regarded as a bright spot within the package.
  • Leave & Time Off Breadth — Feedback suggests generous PTO, paid sick days and holidays, and flexible PTO alongside remote-work options. These elements indicate broad time-off provisions available on paper.

Tiger Analytics Insights

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The Company
HQ: Santa Clara, CA
5,000 Employees
Year Founded: 2011

What We Do

Tiger Analytics is a global leader in AI and Analytics, helping Fortune 1000 companies solve their toughest challenges. We offer fullstack AI and analytics services & solutions to empower businesses to achieve real outcomes and value at scale. We are on a mission to push the boundaries of what AI and analytics can do to help enterprises navigate uncertainty and move forward decisively. Our purpose is to provide certainty to shape a better tomorrow. Our team of 4000+ technologists and consultants are based in the US, Canada, the UK, India, Singapore, and Australia, working closely with clients across CPG, Retail, Insurance, BFS, Manufacturing, Life Sciences, and Healthcare. We are Great Place to Work-Certified™ and have been recognized by analyst firms such as Forrester, Gartner, Everest, ISG, HFS, and others. Ranked among the ‘Best’ and ‘Fastest Growing’ analytics firms lists by Inc., Financial Times, Economic Times and Analytics India Magazine. In India, our offices are located in Chennai, Hyderabad and Bangalore.

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