Machine Learning Engineer, Wave
CA$101-113k
+ Bonus Structure
Financial services for small business owners
Job no longer available
Financial services for small business owners
201-500 employees
Job no longer available
CA$101-113k
+ Bonus Structure
201-500 employees
Company mission
To create a future where small business owners can manage their finances fearlessly.
Role
Who you are
- This role is perfect for a technical lead-in-the-making who wants to ensure our AI systems are efficient, reliable, and deeply integrated into our organizational goals
- Experience: Minimum of 4–6 years of professional experience in machine learning engineering, with a proven track record of deploying models into production environments
- Education: Degree/Diploma in Computer Science, Engineering, Data Science, Applied AI, Machine Learning, or some combination
- Technical Depth: Deep understanding of the modern AI stack, including data ingestion workflows and experience working with curated data warehouses like Snowflake, Databricks, or Redshift
- Cloud Proficiency: At least 3 years of hands-on experience with AWS infrastructure, specifically SageMaker, Spark/AWS Glue, and Infrastructure as Code (IaC) using Terraform
- Orchestration Expert: High proficiency in managing multi-stage workflows using Airflow or similar orchestration systems to automate training and deployment cycles
- MLOps Toolkit: Practical experience with MLflow, Kubeflow, or SageMaker Feature Store to support the end-to-end machine learning lifecycle
- Governance Mindset: Familiarity with model governance practices (lineage, fairness, and privacy) and experience using data cataloging tools for compliance
- Communication: Strong ability to communicate complex technical concepts to non-technical stakeholders and influence project direction
- Industry Context: Experience in FinTech or SaaS environments is a significant advantage
What the job involves
- As a Machine Learning Engineer II, you will be a key contributor to the design, development, and deployment of our foundational AI and ML models
- You will build robust, scalable machine learning pipelines and platforms that support advanced analytics and business intelligence
- Design & Execute: Take ownership of the design and implementation of modern AI stack components, including data ingestion for AI/ML workloads and end-to-end model training and serving pipelines
- Scale & Optimize: Build and manage fault-tolerant AI platforms that scale economically. You will balance the maintenance of legacy models with the rapid development of advanced, scalable solutions
- Mentor & Collaborate: Provide technical mentorship to junior engineers and foster a collaborative environment. You will act as a bridge between data science and production engineering
- Drive Technical Excellence: Promote best practices in coding, testing, and MLOps. You thrive in ambiguous conditions by independently identifying opportunities to optimize model pipelines and improve AI workflows
- Cross-Functional Integration: Partner with data scientists, product managers, and software engineers to translate business needs into technical requirements and integrate AI solutions into production applications
- Implement Governance: Enforce model quality standards, integrity, and reliability. You will be responsible for implementing model lineage, fairness, and privacy controls within the automated pipelines
- Monitor & Measure: Build monitoring frameworks to track model performance and system KPIs, ensuring our AI initiatives drive measurable business outcomes
Our take
Over 90% of all businesses in North America are zero to five employee companies. These businesses are organising their finances either by paying an expensive accountant, or relying on traditional spreadsheets.
In response, Wave is democratising access to financial services software. While it is not the first to do this, it has taken the flourishing approach of giving away the invoicing and accounting software 100% for free.
The company instead makes money by embedding financial services products within the software. It's these payments and other revenue streams that the startup is now looking to expand to secure more revenue to scale.
While the company has had success so far with its tools, it will need to build a whole suite of products and services in order to compete with the accounting software giants like Xero.
Steph
Company Specialist at Welcome to the Jungle
Insights
-7% employee growth in 12 months
Company
Funding (last 2 of 11 rounds)
Jun 2018
$3.3m
EARLY VC
May 2017
$32m
SERIES D
Total funding: $81.2m
Company benefits
- Work From Where You Work Best: We will always have a welcoming, energizing, and world-class office (in Toronto) with a space for you. Or, if you’re more comfortable working from home, the choice is yours
- We Care About Future You: You will stretch yourself and you will grow at Wave. You will also be supported on this journey with diverse learning experiences, educational allowances, mentorship, and so much more
- We Support the Full You: We make a serious investment in your health & wellness. When we think about benefits we think about body, mind, & soul and we take this stuff very seriously
- We Take Care of the Fundamentals: Fair compensation, all the office perks you’d want, and the various goodies you’d expect from a growing tech company. This is the obvious stuff, but we don’t want you to think we forgot!
Company HQ
Leslieville, Toronto, ON
Leadership
Zahir Khoja
(CEO)Worked at Mastercard as EVP (Global Merchant Solutions and Partnerships) and held several Senior VP positions. Former Vintro Board Member and General Manager (North America) at Afterpay.
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