Senior Machine Learning Engineer

Bits In Glass; Alberta; Hybrid; CAD 90,000 - 120,000; Full time

Job summary

A leading cloud consulting firm in Alberta is seeking an experienced AI/ML Engineer to develop scalable AI solutions and manage the ML lifecycle. The ideal candidate will have over 5 years of experience in machine learning engineering and a strong knowledge of Python and ML tools. This role offers the chance to work in a collaborative environment with up to 20% travel required within Canada and the U.S. Competitive total compensation including a bonus and professional development budget is provided.

Benefits

Annual bonus

Healthcare benefits

Professional development budget

Qualifications

• 5+ years of experience in development of machine learning engineering.
• Strong understanding of the Software Development Lifecycle (SDLC).
• Extensive knowledge and experience with Python, PyTorch, and Scikit-learn.

Responsibilities

• Build AI/ML models using best practices.
• Design and build scalable AI/ML solutions.
• Manage the end-to-end ML lifecycle.

Skills

Machine Learning Engineering

Applied AI

Data Engineering

Python

PyTorch

Scikit-learn

MLOps

Cloud Platforms

Agile Methodologies

Education

BS, MS or PhD in Computer Science, Mathematics, Physics, Engineering

Tools

Databricks

Job description

Overview

Do you want to work for an award-winning professional services company? Bits In Glass was voted Canada’s Great Place to Work for three years in a row and the Denver Business Journal Best Places to Work for two years in a row. Bits In Glass has also won numerous Partner of the Year awards from the vendors we partner with. Bits In Glass, or “BIG,” is a great place for energetic IT Professionals to work and grow. As a high-growth firm, we have ample opportunities for advancement, and our company culture is based on getting the job done while having fun!

Responsibilities

• Build AI/ML models using accepted best practices
• Design and build scalable AI/ML solutions, including ML services, agentic workflows, and intelligent automation components
• Develop and deploy production-ready AI systems, ensuring reliability, performance, security, and maintainability.
• Manage the end-to-end ML lifecycle, including experimentation, model training, evaluation, versioning, and deployment
• Define and implement strategies to move AI initiatives from proof-of-concept to production at scale.
• Establishing success metrics, benchmarks, and evaluation frameworks to measure business and technical impact.
• Partner with stakeholders to create roadmaps for AI adoption, balancing quality and governance
• Collaborate with engineering teams on data acquisition pipelines, data migration strategies, and feature engineering.
• Work with cloud and platform teams to ensure AI solutions integrate seamlessly with enterprise infrastructure.
• Partner with process automation teams (e.g., RPA, workflow orchestration, low-code platforms) to embed AI into business processes.
• Design AI-powered automation solutions that enhance decision-making, efficiency, and scalability.
• Translate business requirements into technical solutions that align with automation and enterprise architecture standards.
• Stay current with the latest advancements in AI/ML and generative AI, and evaluate their applicability to client use cases.
• Transform emerging techniques into practical, value-driven solutions.
• Contribute to internal accelerators, reusable assets, and technical standards within the consulting practice.

Qualifications

• BS, MS or PhD in Computer Science, Mathematics, Physics, Engineering or related
• 5+ years of experience in development of machine learning engineering, applied AI, or data engineering, with a strong focus on production systems.
• Strong understanding of the Software Development Lifecycle (SDLC) and Agile delivery for customers, with a consulting mindset.
• Extensive knowledge and experience with relevant program languages and tools like Python, PyTorch and Scikit-learn
• Proven experience with MLOps practices, including model deployment, monitoring, and lifecycle management.
• Experience working with enterprise data pipelines and large-scale datasets.
• Eager to research and learn new topics and technologies
• Experience with hyperscaler environments, like Microsoft Azure, Amazon AWS, Google GCP, etc. and the associated ML/AI suites

Preferred Qualifications

• Experience with LLMs, agentic systems, and generative AI applications.
• Experience in a consulting or client-facing environment.
• Experience working within Databricks

***This is a remote role which may occasionally require up to 20% travel within Canada and the United States.

BIG offers a competitive total compensation plan, including an annual bonus, healthcare benefits and a professional development budget.

Bits In Glass (BIG) is a fast-growing global cloud consulting firm with a presence across the US, Canada, the UK, and India. Our team of passionate technology experts partners with organizations of all sizes to modernize, automate, and transform their businesses using cutting-edge platforms such as Appian, MuleSoft, Pega, Creatio, Boomi, and Databricks. At BIG, we focus on delivering real business impact through innovation, collaboration, and the smart use of technology.