Posted 12 months ago
Machine Learning Engineer
@ Architech Solutions
Toronto, Ontario
Overview
Architech Solutions is hiring a full-time Machine Learning Engineer on a contract rate of CAD $70-85 per hour. The role builds and optimizes customer churn prediction models, feature engineering pipelines and monitoring, and works with business teams to turn insights into retention strategies.
Pay:
$70–$85 an hour
Responsibilities:
- Build scalable churn prediction machine learning models
- Design feature engineering pipelines
- Monitor model performance
- Translate insights into retention strategies with business teams
Requirements summary:
- Experience with customer churn predictions
- Proficiency in Python or R, SQL and Databricks
- Experience with Scikit-learn, TensorFlow or PyTorch
- Strong feature engineering and large-scale data processing
- Knowledge of statistical modelling and predictive analytics
- Familiarity with Azure, AWS or GCP and Spark
Tools & skills
Source and dates
Employer career site / ATS feed · ultipro
- Employer posting date
- 2025-11-20
- First seen by our source
- 2026-10-12
- Source record updated
- 2026-10-19
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Department | Data & analytics |
| Hours per week | 40 (estimated) |
| Work setting | Office |
| Position | Mostly sitting |
| Physical demands | physical low · computer high |
| Languages | English |
| Encouraged to apply | Racialized people, People with disabilities |
| Perks mentioned | Performance bonus |
Summary and details written by AI from the posting; the employer’s posting is the authority.
Architech Solutions
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.
Redesigning workflows with AI. Deploying them in production. Proving the results.
Full company description
Most AI projects never make it to production. They start with good intentions, a pilot here, a proof of concept there, but without a clear outcome defined, the right workflows identified, or a plan to deploy and measure, they stall. At Architech, we take a different approach. AI creates value when workflows are redesigned, not when tasks are automated. We work with operationally complex organizations to redesign their workflows with AI and put them into production. Outcomes are measured in production, not claimed in presentations. We've been designing and building critical business systems for 22 years. Today, we’re focused on bringing that same rigour to help leaders move from AI exploration to measurable results in production. If you're ready to move beyond pilots, we'd love to talk.
- LinkedIn followers
- 40,148
- People associated on LinkedIn
- 252
- Reported office locations
- 180 John St, Toronto, Ontario M5T 1X5, CA
- pl. Juliusza Kossaka 3/8, Kraków, 31-106 31-106, PL
- Botega, CO
- Hydrabad, IN
- Business categories
- Software
- Enterprise Applications
- Web Development
- Consumer Applications
- Cloud Computing
- Mobile
- Other recorded names
- Architech Solutions
- Architech
- Specialties
- UI/UX Design
- Software Architecture
- Cloud-Native Development
- Mobile Development
- API Development
- Platform Development
- DevOps
- DevSecOps
- Cloud Application Managed Services
- Application Modernization
- Digital Transformation
- Agile Engineering
- Design Thinking
- Artificial Intelligence
- AI Powered Applications
- AI Agents
- Agentic AI
- MCP
- ML Ops
- Predictive Analytics
- AI Ops
- AI Managed Services
- AI Search
- AI Powered Automation
- and AI Powered Document Intelligent
- 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.
Most AI projects never make it to production. They start with good intentions, a pilot here, a proof of concept there, but without a clear outcome defined, the right workflows identified, or a plan to deploy and measure, they stall. At Architech, we take a different approach. AI creates value when workflows are redesigned, not when tasks are automated. We work with operationally complex organizations to redesign…
| Field | Value |
|---|---|
| Industry | Software Development |
| Company size | 51-200 employees |
| Headquarters | Toronto, Ontario |
| Organization type | Privately Held |
| Year founded | 2004 |
| Specialties | UI/UX DesignSoftware ArchitectureCloud-Native DevelopmentMobile DevelopmentAPI DevelopmentPlatform DevelopmentDevOpsDevSecOpsCloud Application Managed ServicesApplication Modernization |
| Open jobs on Jobsy | 6 |
| View page |
Contract Rate:
CAD $70-85/hr
Join Us in Building the Future
At Architech, we don’t just ship software. We partner with North America’s leading brands to modernize legacy platforms, embed AI into real operations, and launch digital products that transform business outcomes. Our engineers and designers harness cloud-native tools, autonomous agents, data-driven insights, and GenAI to drive measurable impact - replatforming systems in the cloud, optimizing customer journeys, or accelerating AI adoption across the enterprise. You’ll work at the intersection of strategy and execution, solving complex problems alongside smart, curious teammates across Canada and Poland. Backed by 20+ years of experience, a drive for excellence, and a culture rooted in growth and collaboration, this is where you thrive if you’re looking to deliver meaningful, high-stakes software solutions.
We’re Building a More Inclusive Tech Industry
We believe diversity leads to better outcomes. Nearly half of our team was born outside of Canada, and we speak 19+ languages. We’re 31% women, 57% BIPOC, and 14% LGBTQIA+. We’ve doubled the number of women in tech roles in the past year, and maintain a 0% gender pay gap across our delivery and technology teams. Inclusion here isn’t a buzzword, it’s backed by data, policy, and accountability.
How We Work Together
- We’re a close-knit, collaborative group who care about doing excellent work, and doing it with integrity. Our values shape how we show up every day:
- Think Big – Dream it, plan it, ship it
- Be Open & Collaborate – Diverse minds build better solutions
- Never Fail a Client – Own the outcome
- Grow Our People – Feedback, learning, leadership
- Do the Right Thing – Even when it’s hard
- Embrace Change – Adapt fast, stay curious
Our people say it best: “Employees of different backgrounds interact well within our company” - and 97% agree. Another 96% say “Architech respects individuals and values their differences.” We support continuous growth with learning budgets, internal bootcamps, certification bonuses, summit days, and more. It’s not just work - it’s a place to grow, lead, and build things that matter. And this is just the beginning.
Job Description:
Lead the development and optimization of churn prediction models to identify customers at risk of leaving. Responsibilities include building scalable machine learning models, designing feature engineering pipelines, monitoring performance, and collaborating with business teams to translate insights into retention strategies.
Key Skills
- Experience with Customer Churn Predictions
- Proficiency in Python/R, SQL, DataBricks and data manipulation libraries.
- Experience with machine learning frameworks (Scikit-learn, TensorFlow, PyTorch).
- Strong background in feature engineering and large-scale data processing.
- Knowledge of statistical modelling and predictive analytics.
- Familiarity with cloud platforms (Azure, AWS, GCP) and big data tools (Spark, Databricks).
- Excellent communication for technical and non-technical audiences.
Architech is an equal opportunity employer committed to diversity. Should you require any accommodation prior to or during the interview process, please indicate this during the interview process. We strongly encourage applications from racialized people, people with disabilities, people from gender and sexually diverse communities and/or people with intersectional identities.
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