Machine Learning Engineer II

Wave HQ

. 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.

Posted 4/21/2026full-timeRemote • 🇨🇦 CanadaMid-LevelSenior💰 CA$101,000 - CA$113,000 per yearWebsite

Tech Stack

Tools & technologies

AirflowAmazon RedshiftAWSSparkTerraform

About the role

Key responsibilities & impact

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.
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.
Provide technical mentorship to junior engineers and foster a collaborative environment. You will act as a bridge between data science and production engineering.
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.
Partner with data scientists, product managers, and software engineers to translate business needs into technical requirements and integrate AI solutions into production applications.
Enforce model quality standards, integrity, and reliability. You will be responsible for implementing model lineage, fairness, and privacy controls within the automated pipelines.
Build monitoring frameworks to track model performance and system KPIs, ensuring our AI initiatives drive measurable business outcomes.

Requirements

What you’ll need

Minimum of 4–6 years of professional experience in machine learning engineering, with a proven track record of deploying models into production environments.
Degree/Diploma in Computer Science, Engineering, Data Science, Applied AI, Machine Learning, or some combination.
Deep understanding of the modern AI stack, including data ingestion workflows and experience working with curated data warehouses like Snowflake, Databricks, or Redshift.
At least 3 years of hands-on experience with AWS infrastructure, specifically SageMaker, Spark/AWS Glue, and Infrastructure as Code (IaC) using Terraform.
High proficiency in managing multi-stage workflows using Airflow or similar orchestration systems to automate training and deployment cycles.
Practical experience with MLflow, Kubeflow, or SageMaker Feature Store to support the end-to-end machine learning lifecycle.
Familiarity with model governance practices (lineage, fairness, and privacy) and experience using data cataloging tools for compliance.
Strong ability to communicate complex technical concepts to non-technical stakeholders and influence project direction.
Experience in FinTech or SaaS environments is a significant advantage.

Benefits

Comp & perks

🌐 Worldwide ❌ Jobs You've Hidden ⭐️ Saved Jobs ✅ Applied Jobs ✉️ Email Alerts 👤 Account Wave HQ Website LinkedIn All Job Openings 201 - 500 employees Founded 2010 💸 Finance 💳 Fintech ☁️ SaaS Finance
Fintech
SaaS Wave HQ is a financial services company that provides a suite of money management tools designed to help small business owners. The platform offers features such as invoicing, online payments, accounting, and payroll, all in one integrated system. Wave HQ aims to simplify the financial management process for small business owners, enabling them to manage invoices, track income and expenses, and process payroll efficiently. The company is targeted towards freelancers, contractors, consultants, and self-employed entrepreneurs, providing them with a user-friendly dashboard and access to bookkeeping, accounting, and payroll coaching. Machine Learning Engineer II Job not on LinkedIn 🔥 1 minute ago 🇨🇦 Canada – Remote 💵 $101k - $113k / year ⏰ Full Time 🟡 Mid-level 🟠 Senior 🤖 Machine Learning Engineer Airflow Amazon Redshift AWS Spark Terraform Apply Now Find Hiring Managers Customize resume for this job Report problem ☆ Save ☑️ Mark as applied ❌ Hide 📋 Description
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.
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.
Provide technical mentorship to junior engineers and foster a collaborative environment. You will act as a bridge between data science and production engineering.
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.
Partner with data scientists, product managers, and software engineers to translate business needs into technical requirements and integrate AI solutions into production applications.
Enforce model quality standards, integrity, and reliability. You will be responsible for implementing model lineage, fairness, and privacy controls within the automated pipelines.
Build monitoring frameworks to track model performance and system KPIs, ensuring our AI initiatives drive measurable business outcomes. 🎯 Requirements
Minimum of 4–6 years of professional experience in machine learning engineering, with a proven track record of deploying models into production environments.
Degree/Diploma in Computer Science, Engineering, Data Science, Applied AI, Machine Learning, or some combination.
Deep understanding of the modern AI stack, including data ingestion workflows and experience working with curated data warehouses like Snowflake, Databricks, or Redshift.
At least 3 years of hands-on experience with AWS infrastructure, specifically SageMaker, Spark/AWS Glue, and Infrastructure as Code (IaC) using Terraform.
High proficiency in managing multi-stage workflows using Airflow or similar orchestration systems to automate training and deployment cycles.
Practical experience with MLflow, Kubeflow, or SageMaker Feature Store to support the end-to-end machine learning lifecycle.
Familiarity with model governance practices (lineage, fairness, and privacy) and experience using data cataloging tools for compliance.
Strong ability to communicate complex technical concepts to non-technical stakeholders and influence project direction.
Experience in FinTech or SaaS environments is a significant advantage. Apply Now 📊 Check your resume score for this job Improve your chances of getting an interview by checking your resume score before you apply. Check Resume Score Similar Jobs Lead Machine Learning Engineer – Team Lead 🔥 4 hours ago Datatonic 51 - 200 🤖 Artificial Intelligence 🛍️ eCommerce 📡 Telecommunications Website LinkedIn All Job Openings Lead ML Engineer responsible for guiding a team to deliver innovative ML solutions at Datatonic. Overseeing project management while ensuring technical excellence and team collaboration. 🇨🇦 Canada – Remote 💵 CA$150k - CA$185k / year 💰 Pre Seed Round on 2013-01 ⏰ Full Time 🟠 Senior 🤖 Machine Learning Engineer Cloud Google Cloud Platform PyTorch Scikit-Learn Tensorflow Machine Learning Engineer 🔥 22 hours ago Datatonic 51 - 200 🤖 Artificial Intelligence 🛍️ eCommerce 📡 Telecommunications Website LinkedIn All Job Openings Machine Learning Engineer developing AI and data-driven solutions at Datatonic. Engaging in technical projects and leading client discussions with expertise in Python and machine learning. 🇨🇦 Canada – Remote 💰 Pre Seed Round on 2013-01 ⏰ Full Time 🟡 Mid-level 🟠 Senior 🤖 Machine Learning Engineer AWS Azure Cloud Flask Python SQL Machine Learning Engineer 🕒 Yesterday Reddit, Inc. 501 - 1000 👥 B2C 📱 Media 🌍 Social Impact Website LinkedIn All Job Openings Machine Learning Engineer designing and building production ML systems at Reddit. Tackling complex ML problems and influencing user experience and business outcomes. 🇨🇦 Canada – Remote ⏰ Full Time 🟡 Mid-level 🟠 Senior 🤖 Machine Learning Engineer Java Python PyTorch Tensorflow Go Machine Learning Engineer II, Fraud 🕒 Yesterday Affirm 1001 - 5000 💳 Fintech 👥 B2C 🛍️ eCommerce Website LinkedIn All Job Openings Machine Learning Engineer developing fraud prediction models for Affirm. Collaborating with cross-functional teams and building real-time transaction decision systems. 🇨🇦 Canada – Remote 💵 $125k - $175k / year 💰 Post-IPO Equity on 2021-01 ⏰ Full Time 🟢 Junior 🟡 Mid-level 🤖 Machine Learning Engineer Airflow Python PyTorch Ray Spark Senior Machine Learning Engineer 🕒 3 days ago DraftKings Inc. 1001 - 5000 🎲 Gambling 🎮 Gaming 👥 B2C Website LinkedIn All Job Openings Senior Machine Learning Engineer developing ML infrastructure for DraftKings' Casino, Sportsbook, and Fantasy products. Collaborating with Data Science and Engineering teams to streamline workflows. 🇨🇦 Canada – Remote ⏰ Full Time 🟠 Senior 🤖 Machine Learning Engineer AWS Cloud Python Spark SQL View More Machine Learning Engineer Jobs 🌐 Worldwide Built by Lior Neu-ner. I'd love to hear your feedback — Get in touch via DM or support@remoterocketship.com Search Search Jobs by country Search jobs by city Search jobs by job title Search entry-level jobs Search junior-level jobs Search senior-level jobs Search jobs by tech stack Search jobs by contract type Search remote internships Search remote part-time jobs Remote jobs Anywhere in the World Companies Hiring Anywhere in the World Companies Hiring Sales People Anywhere in the World Companies Hiring Software Engineers Anywhere in the World Resources Advice Tips for finding remote jobs Interview questions and answers Resume examples Cover letter examples Post a job Affiliates Privacy policy Terms of service Job board SEO course AI Apply Copilot OpenClaw job finder Jobs by Country Remote jobs anywhere in the world (Worldwide remote jobs) Remote jobs United States Remote jobs Australia Remote jobs Brazil Remote jobs Canada Remote jobs France Remote jobs Ireland Remote jobs Germany Remote jobs Netherlands Remote jobs Spain Remote jobs UK Popular Jobs Remote data analyst jobs Remote customer support jobs Remote executive assistant jobs Remote marketing jobs Remote product designer jobs Remote product manager jobs Remote project manager jobs Remote recruiter jobs Remote sales jobs Remote software engineer jobs Jobs by Type Remote full-time jobs Remote part-time jobs Remote contract jobs Remote internship jobs Remote entry-level jobs Remote jobs with no experience required Remote junior jobs (1-3 years of experience) Digital nomad jobs Remote jobs with no degree required Freelance remote jobs Temporary remote jobs Remote jobs hiring now Stay at home mom jobs

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Hard Skills & Tools

machine learning engineeringdata ingestionmodel trainingmodel servingMLOpsmodel governanceInfrastructure as Codeworkflow orchestrationdata catalogingmodel performance monitoring

Soft Skills

technical mentorshipcollaborationcommunicationproblem-solvinginfluenceadaptabilityoptimizing workflowsproject direction