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Added 7 mins ago
Senior Software Developer
ADGA Group
Ottawa, ON
$100,000 to $125,000 CAD / year
Full-time
ADGA Group is a Canadian-owned defence and security company that provides integrated, mission-critical technical solutions to Government and industry, specializing in C5ISRT, simulation and…
Added 23 mins ago
Senior Conversation Bot Engineer - Dialogflow CX
Quantiphi
Toronto, ON
Full-time
…with global enterprises to deliver large-scale digital, cloud, and AI-driven transformation.…
Added 53 mins ago
System Engineer
MCAP
Cambridge, ON · Greater Kitchener-Cambridge-Waterloo Metropolitan Area
Full-time
Conduct research as directed on software and systems products to justify recommendations and to support purchasing efforts.
Added 54 mins ago
EIT - environment
GHD Group Pty Ltd
Bedford, NS
Bring your curiosity and passion to the technical challenges we solve at GHD. Then see how everyone gets behind you. With commitment, there’s no idea too big, no dream too far. We strive to…
Added 1 hour ago
Software Engineer Co-op Student (AI) (4-month contract)
Foresters Financial
Toronto, ON
Full-time
The Software Engineer Co-op Student will join the AI & Enterprise Applications team and contribute to the design, development, and deployment of innovative software solutions and AI-powered…
Added 1 hour ago
Senior Architecte IA/ML | Senior AI/ML Architect, Services professionnels pour le secteur public | Public Sector Professional Services
Amazon
Montreal, QC
Are you passionate about developing machine learning (ML) and Generative AI (GenAI) solutions? Amazon has been investing in research and application of ML for decades. We are looking for…
Added 1 hour ago
Business Development Manager, Enterprise Wireless & Network Services
ArcLinx Technology
Vancouver, BC
$100,000 to $120,000 CAD / year
Full-time
You are a business development professional who sells outcomes, not boxes. You build trust with IT leaders, facilities teams, and executives, and you turn it into long-term partnerships.…
Added 1 hour ago
Senior PSA (Probabilistic Safety) Analyst
AtkinsRéalis
Mississauga, ON
Full-time
Make the most of diverse opportunities for training and professional development to grow your skills and expertise.
Added 1 hour ago
Senior PSA (Probabilistic Safety) Analyst
AtkinsRéalis
Mississauga, ON
Full-time
Make the most of diverse opportunities for training and professional development to grow your skills and expertise.
Added 1 hour ago
Founding Engineer, Physical AI + Computer Vision (Equity-Based)
Shipped
Canada
Contract
We’re looking for an exceptional Founding Engineer, Physical AI + Computer Vision to work directly with the founder and help define and build Shipped’s core technology.
Added 1 hour ago
Algorithm Software Engineer
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Full-time
Research and develop new algorithms and methods to leverage next generation hardware.
Added 1 hour ago
Project Engineer - Integrated Projects
City of Vancouver
Vancouver, BC
The Project Engineer will work collaboratively with multidisciplinary civil consultants, third party utility providers, interdepartmentally within Engineering Services and with other CoV…
Added 2 hours ago
Engineer (Physical AI)
Renesas Electronics
Ottawa, ON
Full-time
We are seeking an entry level Engineer (Physical AI) to join the Pathfinding Studio within the Engineering Innovation Office. In this role, you will research and develop next generation…
Added 2 hours ago
Machine Learning Engineer
Placement Group
Canada
Full-time
If you're an early- to mid-career ML engineer who wants hands-on impact and fast growth, this is for you.
Added 2 hours ago
Engineer (Physical AI)
Renesas Electronics
Ottawa, ON
Full-time
We are seeking an entry level Engineer (Physical AI) to join the Pathfinding Studio within the Engineering Innovation Office. In this role, you will research and develop next generation…
Added 2 hours ago
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WSP
Lethbridge, AB
Full-time
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Added 2 hours ago
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Markham, ON
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Materials Engineer - NETE
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Montreal, QC · Halifax, NS
Full-time
Weir Canada is seeking a Materials Engineer to join the Naval Engineering Test Establishment (NETE), where you will work alongside engineers, technologists, military personnel, and industry…
Added 3 hours ago
Junior Environmental Scientist, Engineer in Training or Technologist
Worley
Calgary, AB
Full-time
…practice, where technical expertise, environmental stewardship, and practical problem solving come together to help clients manage environmental liabilities, restore impacted sites, and…
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Vancouver, BC
Working closely with our senior engineers and designers, your primary role will be to act as a technical resource on challenging projects. You will apply analytical, conceptual, research,…
Added 4 hours ago
Designer, Development (Service)
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Bolton, ON
Full-time
Regularly provide feedback to product development teams: present project updates at service issue review meetings, attend design reviews to identify risks, submit continuous improvement…
Added 4 hours ago
Applications Engineer
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Bolton, ON
Full-time
Husky TechnologiesTM offers a wealth of opportunity for personal growth and development. Most importantly, Husky Technologies TM offers an opportunity to work with – and be challenged by –…
Added 4 hours ago
Operations Support Engineer
Shell
Corunna, ON
Full-time
The Operations Support Engineer provides process engineering support to the 24x7 production organization to ensure excellence in process safety, reliability, margin, energy optimization,…
Added 4 hours ago
Intermediate Structural Engineer
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Full-time
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Jobber

Staff Data Scientist, Applied ML

Vancouver, BC, Canada

Pay: This role has a minimum annual salary of $145,900 CAD, a midpoint of $171,600 CAD and a maximum salary of $197,400 CAD designed to reflect the progression from learning the ropes to truly excelling.
Job type: Full-time
Apply by: Oct 29, 2026
Posting language: English
Posted: Sep 29, 2026

Apply About employer

Applications open in a new tab.

Original job description

Are you a Machine Learning practitioner who is technically deep and commercially sharp?

If so, this might be the role for you! We're looking for a Staff Data Scientist, Applied Machine Learning (ML) to join our growing Data Science team.

Jobber exists to help people in small businesses be successful. We work with small home service businesses, like your local plumbers, painters, and landscapers, to transform the way service is delivered through technology. With Jobber they can quote, schedule, invoice, and collect payments from their customers, while providing an easy and professional customer experience. Running a small business today isn't like it used to be - the way we consume and deliver service is changing rapidly, technology is evolving, and customers expect more. That's why we put the power and flexibility in their hands to run their businesses how, where, and when they want!

Our culture of transparency, inclusivity, collaboration, and innovation has been recognized by Great Place to Work, Canada's Most Admired Corporate Cultures, and more. Jobber has also been named on the Globe and Mail's Canada's Top Growing Companies list, and Deloitte Canada's Technology Fast 50™, Enterprise Fast 15, and Technology Fast 500™ lists. With an Executive team that has over thirty years of industry experience of leading the way, we've come a long way from our first customer in 2011 - but we've just scratched the surface of what we want to accomplish for our customers.

We help employees grow professionally; we have a ton of onboarding resources, tutorials, hackathons and buddies to support learnings and provide opportunities to innovate. We have a range of experience levels on teams which allows for mentor/mentee opportunities. Leaders at Jobber work with empathy and support employees to build healthy work-life harmony. Bring your dedication and passion to this job to fulfill your goals.

The team:

Similar to how Jobber empowers small businesses with the tools and insights they need to succeed, the Strategy and Analytics Department ensures our people at Jobber have the tooling, data insights, and strategic direction to excel in our shared mission. We turn data into actionable insights, and critical business needs into impactful software, working with multiple teams and departments across the company. Strategy & Analytics serves as a central hub that drives business outcomes in all corners of Jobber's ecosystem.

Within that department, Data Science is the predictive and prescriptive arm. We're a small, hungry team with an outsized footprint. We work in two-week sprints, demo to the whole department, and expect each other to bring a point of view rather than a ticket.

SignalGraph is our next major project: a company-wide metric graph that connects organizational activity and outcomes so teams can trace metric movement to root causes, investigate faster, and make better decisions.

The role:

Reporting to the Manager, Data Science, the Staff Data Scientist, Applied Machine Learning will own models and systems for automated decisioning. You will train and evaluate models using techniques such as graph representation learning, transformer architectures, and ranking, and engineer them to serve reliably in real time and at scale inside Jobber's product.

This is a senior individual contributor role with strong architectural scope. You'll be the person who decides how ML systems at Jobber are built, evaluated, and trusted and you'll be doing it against a dataset most companies our size don't have: high-velocity SaaS event data, scheduling data, and payments data across hundreds of thousands of service professionals and millions of their clients, plus a rich body of unstructured sales and support text.

The Staff Data Scientist, Applied Machine Learning will:

Continue building, improving, and maintaining SignalGraph: evolve metric-family contracts, keep segment and causal-edge catalogs trustworthy, operate the Neo4j and series-refresh pipeline, and strengthen investigation diagnostics so teams can trace metric changes to root causes and make faster decisions from governed evidence..
Design, build, and evaluate retrieval-augmented generation (RAG) systems on top of that graph. You’ll own retrieval quality, context management, and the evaluation harness that proves the system is actually right, not just fluent.
Own production ML end-to-end: training pipelines, real-time serving, monitoring, drift detection, and retraining. When a model is live, its uptime, latency, and accuracy are yours.
Establish systematic evaluation and regression testing as a standard for the team - so model and LLM system quality is measured and defended over time rather than assessed once at launch.
Set the technical bar and multiply the team: drive MLOps and ML engineering standards, shape our feature store and platform roadmap, review peers' work, and mentor other scientists on graph and deep learning methods.
Partner directly with senior leadership. Much of what you build will be used by Senior Leaders, Customer Analytics, Business Intelligence, and Product to make decisions against Jobber's North Star goals. You'll present your own work, defend your assumptions, and help cross-functional partners reframe how they approach a problem.
Stay current, and bring it back. We expect this role to be the most informed person at Jobber on developments in AI/ML methodologically, not just as a consumer of tools, and to translate that into shipped capability.

To be successful, you should have:

Production ML experience, end-to-end. You've trained, deployed, served, and maintained models that acted on real users (not just scored offline) You've learned the hard lessons about retraining, drift, and technical debt that come with it.
A strong statistics foundation. You can reason about bias and variance, justify a loss function, and tell signal from noise without hand-waving.
Expert SQL and production-grade Python skills.
Depth in modern ML methods: Deep learning and neural architectures, transformers/BERT-family models, RNN/CNN, ranking, and representation learning, with hands-on experience applying LLMs in production systems, including RAG and context management.
Experience designing for the real cost of being wrong. You've built or tuned custom and asymmetric loss functions where a miss in one direction is far more expensive than the other, and you can explain the business reasoning behind the choice.
Experience with large data in production environments and the platforms that support it. ML/AI platforms such as Snowflake, orchestration with Apache Airflow, and cloud infrastructure (AWS strongly preferred; GCP or Azure equivalent considered).
Strong communication and stakeholder alignment skills. This team's work only lands if everyone shares the same understanding of what the data means. You can take a room of technical and non-technical partners from confusion to alignment, present uncertainty honestly, and influence without authority.
Ownership of quality over shipping speed alone. You want to know why something works and how to make it better. You don't accept a model's current performance as its ceiling, and you don't outsource your understanding of your own code to an AI assistant.

It would be nice if you had:

Graph experience: Graph theory, graph neural networks, knowledge graphs, or graph databases such as Neo4j. Rare, and the single most valuable thing you could bring to this role.
A software engineering background: Services and model serving (REST/gRPC), Docker/Kubernetes, CI/CD, feature stores.
Experience with Snowflake, including Snowpark and Snowpark Container Services, or a comparable path from warehouse to deployed model.
Experience building LLM evaluation infrastructure, safety layers, or LLMOps for customer-facing AI.
Exposure to risk, fraud, or fintech modelling, or to recommendation and ranking systems at scale.

Compensation:

At Jobber, we also believe that compensation should be transparent, fair, and supportive of your experience and growth. This role has a minimum annual salary of $145,900 CAD, a midpoint of $171,600 CAD and a maximum salary of $197,400 CAD designed to reflect the progression from learning the ropes to truly excelling.

We design our compensation to reflect each new hire's skills, experience, and the complexity of the role, ensuring a fair and competitive salary.

Our range is intentionally broad to support growth and long-term impact, with fully established hires typically starting around the midpoint. The higher end of the range is reserved for those who have demonstrated deep expertise and lasting contributions, while offers below the midpoint reflect strong potential with room to develop. This approach ensures that compensation aligns with both an individual's current capabilities and their opportunity for future growth.

Base salary is just one part of a total compensation package that will include equity rewards, annual stipends for health and wellness, retirement savings matching, and an extended health package with fully paid premiums for body and mind. Your professional growth matters to us too! You'll have access to a dedicated talent development program that includes career coaching and opportunities for career development.

We believe in transparency and open conversations about compensation. If you have any questions about our approach, we're happy to discuss them throughout the hiring process!

What you can expect from Jobber:

A total compensation package that includes an extended health benefits package with fully paid premiums for both body and mind, matching in RRSP, TFSA or FHSA, and stock options.
A dedicated Talent Development team and access to coaching, learning, and leadership programs to help you grow your career, reach your goals, and unlock your full potential.
A unique opportunity to build, grow, and leave your impact on a $400-billion industry that has no dominant player...yet.
To work with a group of people who are humble, supportive, and give a sh*t about our customers.

We believe that diverse teams perform better and that fostering an inclusive work environment is a key part of growing a successful team. We welcome people of diverse backgrounds, experiences, and perspectives. We are an equal opportunity employer, and we are committed to working with applicants requesting accommodation at any stage of the hiring process.

A bit more about us:

Job by job, we’re transforming the way service is delivered. Your lawn care provider, home cleaning service, plumber or painter could use Jobber to better connect with their customers, save time in the office, invoice faster, and get paid! We’re bringing tens of thousands of people together with technology to deliver billions of dollars a year in services to happy customers. Jobber exists to help make these small businesses successful, and when they’re successful we all win!

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More about this job

Responsibilities

Own and improve SignalGraph and build graph-based retrieval-augmented generation systems, including retrieval quality, context management, and evaluation. Lead production ML end to end, establish quality and engineering standards, mentor scientists, and partner with senior leaders and cross-functional teams to deliver reliable, scalable decision systems.

Requirements

Requires end-to-end experience training, deploying, serving, and maintaining production ML models, a strong statistical foundation, and expert SQL and production-grade Python skills. Candidates should have hands-on expertise in modern deep learning and LLM methods, production data platforms and cloud infrastructure, and the communication skills to align technical and non-technical stakeholders.

Skills

Production Machine Learning
Statistics
SQL
Python
Deep Learning
Transformers
Ranking Systems
Representation Learning
Large Language Models
Retrieval-Augmented Generation
MLOps
Model Evaluation
Graph Machine Learning
Apache Airflow
Snowflake
AWS

Benefits

Equity Rewards
Health And Wellness Stipends
Retirement Savings Matching
Extended Health Benefits
Fully Paid Health Premiums
Stock Options
Career Coaching
Learning And Leadership Programs

Visa sponsorship

Not detected in the job text

Keywords

SignalGraph
Graph Representation Learning
Graph Neural Networks
Knowledge Graphs
Neo4j
Retrieval-Augmented Generation
Large Language Models
Transformers
BERT
RNN
CNN
Ranking
Production Machine Learning
MLOps
Feature Stores
Model Serving
Model Monitoring
Drift Detection
Evaluation Harness
Regression Testing
SQL
Python
Snowflake
Snowpark
Apache Airflow
AWS
GCP
Azure
Docker
Kubernetes

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