Machine Learning Engineer

Infostrux Solutions Inc.; Montreal (administrative region), Toronto; On-site; CAD 90,000 - 130,000; Full time

Benefits offered by this job

Remote work from home

Flexible schedule

Vacation time (4 weeks)

Device allowance

Professional development

Co-working/social events

Job summary

Infostrux Solutions Inc. is seeking a Machine Learning Engineer to design, build, and deploy ML solutions.

You will work with senior engineers, data teams, and analysts to contribute to model development, data pipelines, and ML operations in a collaborative, technical environment. Ideal candidates are motivated to grow in MLOps, with hands-on cloud experience (AWS/Azure/GCP) and familiarity with modern data platforms.

Qualifications

• Strong foundation in machine learning fundamentals.
• Proficiency in Python and common ML libraries (pandas, scikit-learn, PyTorch or TensorFlow).
• Experience in training and evaluating ML models.
• Exposure to cloud platforms (AWS, Azure, or GCP).
• Familiarity with MLOps concepts such as model tracking, automated pipelines, and monitoring.
• Basic understanding of containerization (Docker or Kubernetes).
• Experience with APIs or production data workflows.
• Interest in responsible AI, security, or governance.

Responsibilities

• Model Development & Implementation: Build and train machine learning models based on project requirements.
• Data Pipeline Support: Develop and maintain data preprocessing workflows and feature pipelines.
• Machine Learning Operations & Deployment: Contribute to ML deployment pipelines, model versioning, and monitoring.
• Cloud & Data Integration: Work with cloud platforms and Snowflake to operationalize ML models.
• Collaboration: Partner with data engineers, analysts, and senior ML engineers to translate business needs into technical solutions.

Skills

Python & ML libraries

ML model training

Cloud platforms

MLOps concepts

Data pipelines

Tools

Docker

Kubernetes

Airflow

MLflow

Snowflake

Databricks

Terraform

SQL

Job description

About Infostrux:

Infostrux is one of North America's fastest-growing data-focused consultancies. Within 18 months of our founding in 2021, Snowflake recognized us at the highest partnership tier—a reflection of our deep expertise and impact.

We help organizations unlock the value of their data by building modern, cloud-native platforms that power analytics, AI, and machine learning. Our work spans the modern data stack—covering data engineering, architecture, integration, and modelling with Snowflake as one of our core partners.

From startups to Fortune 500s across industries like finance, health, gaming, and retail, we design and deliver scalable data solutions that enable faster, smarter, data-driven decisions. And as proud recipients of the Great Place to Work® Certification (2025), we are equally committed to fostering a culture of trust, collaboration, and growth for our people.

Job Summary:

As a Machine Learning Engineer, you will help design, build, and deploy machine learning solutions that support real-world business needs. Working closely with senior engineers, data teams, and analysts, you will contribute to model development, data pipelines, and machine learning operations while gaining hands‑on experience with modern cloud and data platforms. This role is ideal for someone who loves solving practical problems with machine learning, is eager to grow in machine learning operations, and thrives in collaborative, technical environments.

What you'll get to do:

• Model Development & Implementation: Build and train machine learning models based on project requirements, supporting model evaluation, validation, and performance improvements.
• Data Pipeline Support: Develop and maintain data preprocessing workflows and feature pipelines to ensure seamless data processing. Ensure data quality and consistency across ML systems.
• Machine Learning Operations & Deployment: Contribute to ML deployment pipelines, model versioning, and monitoring. Collaborate with senior engineers on CI/CD and automation practices.
• Cloud & Data Integration: Work with cloud platforms (AWS, Azure, GCP) and Snowflake to operationalize Machine Learning models. Integrate Machine Learning components with modern data architecture.
• Collaboration: Partner with data engineers, analysts, and senior ML engineers to translate business needs into technical solutions. Support documentation, testing, and reliability efforts

What you'll bring:

• Strong foundation in machine learning fundamentals
• Proficiency in Python and common ML libraries (pandas, scikit‑learn, PyTorch or TensorFlow)
• Experience in training and evaluating ML models
• Exposure to cloud platforms (AWS, Azure, or GCP)
• Familiarity with MLOps concepts such as model tracking, automated pipelines, and monitoring

Additional Assets:

• Basic understanding of containerization (Docker or Kubernetes)
• Experience working with APIs or production data workflows
• Interest in responsible AI, security, or governance

What we work with:

• Machine Learning: pandas, scikit‑learn, PyTorch
• MLOps: MLflow, Langchain, Langflow, Airflow
• Data: Snowflake, Databricks Lakehouse
• Cloud: AWS, GCP, Azure
• Infra & Orchestration: Docker, Kubernetes, ECS, Terraform
• Languages: Python (primary), SQL

What's in it for you? We're so glad you asked!

You will be surrounded by some of the brightest and most accomplished technical minds in our field. We are a team of very diverse and passionate professionals who love working together and solving problems by leveraging technology to help our customers. We pride ourselves in our outstanding work culture that is grounded in our 8 core values: trust, excellence, integrity, humility, accountability, responsibility, kindness, and fun.

We value our people above all, and we provide a competitive compensation and benefits package to show our team our appreciation for everything they do:

• We are a 100% remote organization and our team members can work from the comfort of their homes, as well as anywhere abroad where they are entitled to work for up to 3 months per year.
• We are strong believers of work‑life integration and we offer a flexible schedule so that our team can manage their own workload and still be there for family and loved ones.
• We offer 4 weeks of vacation annually, in addition to paid personal and sick days, so that our team can unwind, recharge, and enjoy time away for hobbies and family.
• We provide a monthly bring-your-own-device allowance for each team member to choose the computer and phone of their preference (and it is theirs to keep afterwards).
• We strongly believe in professional growth, so we are continuously educating ourselves with regular lunch & learns and industry events, and we invest in professional development and industry-based certifications for everyone in our team.
• We constantly encourage everyone to step outside of their comfort zone and try new things, so we dedicate time each month to work on non‑client work and collaborate on new innovative ideas, and we reward people who experiment and take risks.
• We enjoy getting together and we promote co‑working days and social events in our main locations on a regular basis.

We are committed to creating a diverse environment and are proud to be an equal‑opportunity employer. All qualified applicants will receive consideration for employment without regard to race, colour, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, or age. Please note that you must be legally eligible to work in Canada to be considered for employment, and if selected, you must complete a criminal and credit background check to be hired. Compensation for this role depends on various factors, including seniority, skill level, and location. Compensation structures may also differ based on the type of engagement—contract rates vary from full‑time employee salary ranges. Specific details will be discussed during the hiring process.

We look forward to getting to know you!

infostrux.com/careers | Join Infostrux, where we design scalable, cloud‑based data solutions that enable faster, smarter, data‑driven decisions.