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Posted 51 months ago

Machine Learning Engineer (Canada)

@ Tiger Analytics Inc.

Toronto, Ontario

Full-time5+ years experience
Apply now
SIGNALS

Overview

Tiger Analytics is hiring a full-time Machine Learning Engineer to deploy, validate, monitor and improve data science solutions in production. The role builds scalable ML systems and containerized, reusable data pipelines, working with a global, partly remote team. The posting requires a bachelor's degree or higher in computer science or a related field with 5+ years of experience.

Responsibilities:

  • Deploy, validate, monitor and improve data science solutions
  • Build scalable, high-performance machine learning systems
  • Build reusable production data pipelines for ML models
  • Write production-quality code packaged as containers

Requirements summary:

  • Bachelor's degree or higher in computer science or related field
  • 5+ years of work experience
  • Experience with Big Data projects using structured and unstructured data
  • Ability to troubleshoot production ML model issues
  • Ability to work with a global team

Tools & skills

Source and dates

Employer career site / ATS feed · workable

Employer posting date
2022-09-11
First seen by our source
2026-10-11
Source record updated
2026-10-11

These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.

Job details

SenioritySenior
DepartmentData & analytics
Experience5+ years
Hours per week40 (estimated)
Work settingOffice, Home
PositionMostly sitting
Physical demandsphysical low · computer high
LanguagesEnglish
EducationBachelor’s degree (required)
Fields of studyComputer science

Summary and details written by AI from the posting; the employer’s posting is the authority.

Tiger Analytics Inc.

Saved company profile

Historical company information from a saved The Jobs API profile (LinkedIn/Crunchbase fields). It is not live-verified; figures may have changed. Missing values remain unknown.

We are a global leader in AI and Analytics. We provide certainty to shape a better tomorrow.

Full company description

In a world rife with complexity, we help our customers cut through uncertainty, plan strategically, and execute confidently. We work with them to strategize and operationalize Data and AI-led transformation programs that deliver real value at scale. Our deep understanding of business value chains, agile operating models, platforms approach, and strategic hyperscaler partnerships allow us to engineer cutting-edge Data & AI solutions. We go beyond standard playbooks and best practices, and forge new ones. If you’re keen to reimagine what AI can do for some of the toughest problems out there, come join our team of 5000+ brilliant technologists and consultants. Explore opportunities across our offices in the US, India, Canada, Mexico, UK, Spain, Singapore and Australia.

LinkedIn followers
630,421
People associated on LinkedIn
6,613
Reported office locations
  • 2350 Mission College Blvd, Ste# 495, Santa Clara, CA 95054, US
  • 111 Town Square Pl, Jersey City, New Jersey 07310, US
  • 36 Robinson Rd, Singapore, Singapore 068877, SG
  • 55 E Monroe, Suite 3800, Chicago, Illinois 60603, US
  • 5151 Headquarters Dr, Plano, Texas 75024, US
  • 65 St Paul’s Churchyard, 3rd Floor Paternoster House, London, EC4M 8AB, GB
  • 383 Kent St, Level 17, Sydney, New South Wales 2000, AU
  • 200 Bay St, North Tower, Suite 1200, PO Box 96, Toronto, Ontario M5J 2J2, CA
  • RMZ Millenia Business Park 2, Campus 5, 2nd Floor, No. 143, Kandanchavadi, MGR Road, Perungudi, Chennai, Tamil Nadu 600096, IN
  • Prestige Tech Park, 1st floor Mercury Block, Kadubeesanahalli, Bengaluru, 560103, IN
  • 8th Floor, B block (iSprout), Divyasree Trinity, Hitech City Rd, Madhapur,, Hyderabad, Telangana 500081, IN
  • De Entree 252, Amsterdam, North Holland 1101 EE, NL
Business categories
  • News
  • Consulting
  • Analytics
  • Advertising
  • Big Data
  • Machine Learning
Other recorded names
  • Tiger Analytics
  • Tiger Analytics Inc.
Specialties
  • Machine Learning
  • Predictive Analytics
  • Forecasting
  • Natural Language Processing
  • Computer Vision
  • Cloud Data Platform Engineering
  • Data-as-a-service
  • Lean Data Governance
  • Modern BI & Data Warehousing
  • AI/ML Ops
  • ML Product Engineering
  • Data Engineering
  • Data Modernization
  • and Generative AI
Profile identifies a recruitment agency
No
Reported total investment
0

Currency and observation date were not supplied; this is not a current valuation or a funding round.

In a world rife with complexity, we help our customers cut through uncertainty, plan strategically, and execute confidently. We work with them to strategize and operationalize Data and AI-led transformation programs that deliver real value at scale. Our deep understanding of business value chains, agile operating models, platforms approach, and strategic hyperscaler partnerships allow us to engineer cutting-edge…

FieldValue
IndustryBusiness Consulting and Services
Company size5,001-10,000 employees
HeadquartersSanta Clara, CA
Organization typePrivately Held
Year founded2011
SpecialtiesMachine LearningPredictive AnalyticsForecastingNatural Language ProcessingComputer VisionCloud Data Platform EngineeringData-as-a-serviceLean Data GovernanceModern BI & Data WarehousingAI/ML Ops
Open jobs on Jobsy81
LinkedInView page
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 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.

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