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Added 27 mins ago
Engineering Co-op Student - January 2027
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$65,624 to $68,744 CAD / year
Advancing Your Global Career: Elevate Your Future with Hudbay
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Added 1 hour ago
Senior Software Engineer, Machine Learning
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Reports to: Technical CEO, working directly with our Founding Engineer and Founding Data Scientist
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Added 1 hour ago
Platform Engineer - AI/ML Infrastructure
Tata Consultancy Services
Toronto, ON
$90,000 to $110,000 CAD / year
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…clients, investors, employees, and the communities it serves. With a highly skilled workforce supporting customers from coast to coast, TCS has consistently been recognized as a Top…
Added 1 hour ago
Cloud Platform Engineer
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The Cloud Platform Engineer is responsible for all aspects of our Kubernetes and Docker containers. He/she will be responsible for production support, administration, testing, and…
Added 1 hour ago
Cloud & DevOps Engineer Co-op (May 2027 | 12-16 months)
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Cloud Platform Engineer
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The Cloud Platform Engineer is responsible for all aspects of our Kubernetes and Docker containers. He/she will be responsible for production support, administration, testing, and…

Chorus

Senior Software Engineer, Machine Learning

Toronto, ON, Canada

Job type: Full-time
Apply by: Mar 21, 2027
Experience: 5+ years of relevant software engineering experience, with a track record of owning production systems end to end.
Posting language: English
Posted: Sep 22, 2026

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Original job description

Senior Software Engineer, Machine Learning

Chorus · Toronto, Ontario

Location: Toronto, Ontario, in office ~4 days/week (68 Claremont Street, near Ossington and Queen St. West)

Compensation: 150,000–170,000 CAD + equity

Reports to: Technical CEO, working directly with our Founding Engineer and Founding Data Scientist

Apply here: https://app.careerpuck.com/job-board/chorus-ai/job/atL-2qZE

About Chorus

Chorus is the marketing intelligence platform for nonprofits. We help mission-driven organizations send the right message to the right supporter at the right moment, building a preference profile for every supporter and routing each one to the content they're most likely to act on. Nonprofits that use Chorus raise 10–20% more revenue from their marketing.

We work directly with nonprofits and advocacy organizations in the US and Canada, and alongside some of the sector's leading marketing agencies, reaching campaigns and programs with budgets in the billions, up to and including U.S. presidential campaigns. Our customers include Feeding America and the Human Rights Campaign.

We closed a seed round earlier this year and are seeing early product-market fit: we're closing tens to hundreds of thousands of dollars in new revenue every month. Now we need an experienced engineer to own the product that's driving it.

The role

This is our third non-founder hire. You'll work out of our Toronto office alongside our technical CEO, Founding Data Scientist, and Founding Engineer.

You'll own Automated Personalized Marketing, our product that uses machine learning models to build audience segments in real time. That means three things:

The ML product, end to end. You'll own the system clients use every day: how models are trained, deployed, served, and monitored, and how their output becomes segments a marketer can act on. You own its reliability, and its performance.
The path from model to production. You’ll work closely with the founding data scientist to translate business requirements into machine learning definitions and model designs. You’ll then train the respective models and turn them into production systems, with evaluation that reflects how the models are actually used, not just how they scored offline.
The platform underneath. Our Founding Engineer owns the data platform that feeds it all: ingesting client marketing data, keeping it clean and current, and making it fast enough to segment in real time. You'll collaborate closely with them, shaping what the platform needs to deliver for the ML product and building on top of it.

What you'll bring

5+ years of relevant software engineering experience, with a track record of owning production systems end to end.
Hands-on ML engineering. You've trained machine learning models, deployed them to production, and evaluated how they perform once real users and real data hit them.
Strong engineering fundamentals: testing, CI/CD, observability, and the discipline to keep a small team's codebase healthy as it grows.
Comfort across our backend stack: a Python/FastAPI backend, MongoDB, S3, Redis, Pinecone, and AWS, deployed on Render.
Comfort across our emerging data platform stack: Python and DuckDB on Dagster
Judgment to work independently in an early-stage environment. You set your own direction on ambiguous problems, and you know when something is ready to ship.
Numerical computing and performance optimization at scale. You're comfortable with the linear algebra under our models, including large matrix operations, and you know how to make it fast and memory-efficient on big datasets: vectorization, sparse representations, batching, and profiling to find the real bottleneck.

Bonus points

Martech, CRM, or marketing data experience (email engagement, supporter or donor behavior).
Experience with hexagonal (ports-and-adapters) architecture. It's how our FastAPI backend is structured.
Experience building retrieval or embedding-based systems. We use Pinecone for embedding-based matching in our models.

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More about this job

Responsibilities

You will own the end-to-end machine learning product, including model training, deployment, and performance monitoring. You will collaborate with the founding team to translate business requirements into production-ready machine learning systems.

Requirements

Candidates must have 5+ years of software engineering experience with a strong background in deploying machine learning models to production. Proficiency in Python, backend infrastructure, and performance optimization for large datasets is required.

Skills

Machine Learning
Python
FastAPI
MongoDB
AWS
Redis
Pinecone
DuckDB
Dagster
CI/CD
Observability
Data Engineering
Linear Algebra
Performance Optimization
Software Engineering

Benefits

Equity

Visa sponsorship

Not detected in the job text

Keywords

Machine Learning
Software Engineering
Python
FastAPI
MongoDB
S3
Redis
Pinecone
AWS
Render
DuckDB
Dagster
CI/CD
Observability
Linear Algebra
Vectorization
Sparse Representations
Batching
Profiling
Martech
CRM
Hexagonal Architecture
Embedding-based systems
Marketing Intelligence
Nonprofit

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