Senior Machine Learning Engineer

BDO Canada

London

Hybrid

CAD 84,000 - 128,000

Full time

14 days+

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Benefits offered by this job

Flexible benefits
Market-leading time off policy
Wellness reimbursement

Job summary

BDO Canada is seeking a Senior ML Engineer in London, Ontario, to lead the development of machine learning pipelines and drive client engagements. This role requires strong experience in MLOps and the Microsoft Azure ecosystem, along with advanced programming in Python. The expected salary range is between $84,000 and $128,000, complemented by a supportive, people-first work culture fostering both professional and personal growth.

Qualifications

  • 5+ years of experience in software engineering, including 3 years in MLOps.
  • In-depth knowledge of Azure services for building ML workflows.
  • Strong proficiency in using Databricks and ML libraries like TensorFlow or PyTorch.

Responsibilities

  • Design and implement MLOps pipelines using Databricks and MLflow.
  • Lead client engagements for ML solution delivery and strategy.
  • Automate model lifecycle processes and ensure operational reliability.

Skills

MLOps expertise
Python programming
Azure ecosystem usage
Databricks proficiency
CI/CD practices
Communication skills

Education

Bachelor’s or Master’s degree in Computer Science or related

Tools

Azure Machine Learning
Databricks
MLflow
GitHub Actions
Terraform

Job description

Overview

BDO is a firm built on a foundation of positive relationships with our people and our clients. Each day, our professionals provide exceptional service, helping clients with advice and insight they can trust. In turn, we offer an award‑winning environment that fosters a people‑first culture with a high priority on your personal and professional growth.

Opportunity

BDO Digital is seeking an experienced and technically proficient Senior ML Engineer to join our Technology Advisory Services practice. This role blends technical leadership with hands‑on MLOps development, focusing on delivering scalable, secure, and production‑grade machine learning pipelines using Azure and Databricks. The successful candidate will also lead client engagements, aligning ML initiatives with business objectives to create real‑world impact.

Key Responsibilities
MLOps and Platform Development
  • Design and implement end‑to‑end MLOps pipelines using Databricks, MLflow, and related tools.
  • Build and manage scalable data and feature engineering pipelines in Databricks.
  • Automate model lifecycle processes including training, testing, deployment, and monitoring.
  • Implement CI/CD workflows using tools such as Azure DevOps or GitHub Actions.
  • Ensure operational reliability, performance, and compliance across all ML workflows.
Client and Delivery Management
  • Serve as a primary technical lead for client engagements focused on ML solution delivery.
  • Translate business goals into machine learning strategies and operational plans.
  • Collaborate with cross‑functional teams to integrate models into production environments.
Machine Learning Application
  • Convert data science prototypes into robust, scalable ML solutions.
  • Apply appropriate ML algorithms to structured and unstructured data problems.
  • Evaluate model performance, run experiments, and iterate for improvement.
  • Document ML pipelines and contribute to internal knowledge sharing.
Qualifications
Required
  • Educational Background: A bachelor’s or master’s degree in computer science, data science, engineering or a closely related discipline. A strong academic foundation in algorithms, data structures, machine learning, and distributed systems is essential.
  • Professional Experience: A minimum of 5 years of hands‑on experience in software engineering, data engineering or DevOps, including at least 3 years of direct experience in MLOps or machine learning engineering roles. Proven success in deploying and maintaining machine learning solutions in production environments is expected.
  • In‑depth knowledge of the Microsoft Azure ecosystem, with demonstrated experience using services such as Azure Machine Learning, Azure Data Lake, Azure Kubernetes Service (AKS), and Azure DevOps. Ability to leverage cloud‑native tools to build scalable and secure ML workflows.
  • Very strong proficiency with Databricks, including hands‑on work with Delta Lake, MLflow, and Apache Spark. Experience integrating these tools into MLOps pipelines and optimizing performance and reliability in production.
  • Advanced programming skills in Python, with practical experience using popular machine learning libraries such as scikit‑learn, TensorFlow, and/or PyTorch. Capable of building, tuning, and deploying ML models in real‑world applications.
  • Solid understanding of CI/CD practices, with experience designing and maintaining pipelines using tools like GitHub Actions, Azure DevOps, or Jenkins. Familiarity with infrastructure‑as‑code tools such as Terraform or ARM templates for automating environment provisioning and deployment.
  • Excellent written and verbal communication skills, with the ability to effectively engage with a range of stakeholders, including data scientists, engineers, business partners, and executive leadership. Proven ability to explain technical concepts to non‑technical audiences and influence decision‑making.
Preferred
  • Certifications: Professional certifications such as Databricks Certified Professional or Microsoft Certified, e.g. Azure Solution Architect.
  • Strong knowledge of LLM frameworks and libraries (such as transformers, trl, deepspeed, PyTorch), and exposure to various ML techniques and their practical implementation in production at large scale.
  • Consulting experience and excellent communication and client management skills.
Compensation

The expected range of compensation for this role is $84,000 to $128,000.

Benefits and Culture

Our people‑first approach to talent has earned us a spot among Canada’s Top 100 Employers for 2026. We enable you to engage with how we change and evolve, being a key contributor to the success and growth of BDO in Canada. We help you become a better professional within our services, industries, and markets with extensive opportunities for learning and development. We support your achievement of personal goals outside of the office and making an impact on your community.

Giving back adds up: BDO is actively involved in our communities by supporting local charity initiatives. We support staff with local and national events where you will be given the opportunity to contribute to your community.

We pay for performance with competitive total cash compensation that recognizes and rewards your contribution. We provide flexible benefits from day one, and a market‑leading personal time off policy. We are committed to supporting your overall wellness beyond working hours and provide reimbursement for wellness initiatives that fit your lifestyle.

Everyone counts: We believe every employee should have the opportunity to participate and succeed. Through leadership by our Diversity, Equity and Inclusion Leader, we are committed to a workplace culture of respect, inclusion, and diversity. We recognize and celebrate the valuable differences among each of us, including race, religious beliefs, physical or mental disabilities, age, place of origin, marital status, family status, gender or gender identity and sexual orientation. If you require accommodation to complete the application process, please contact us.

Flexibility: All BDO personnel are expected to spend some of their time working in the office, at the client site, and virtually unless accommodations or alternative work arrangements are in place. Our blended approach supports the flexible needs of our people, the firm and our clients. It’s about creating work experiences that meet everyone’s needs and providing flexibility to adjust when, where and how we work to meet the expectations of the role.

BDO may use artificial intelligence‑enabled tools to support certain aspects of the recruitment process. While these tools assist our teams, our use of AI does not replace human decision making, and all employment‑related outcomes are made by BDO personnel.

More information on BDO Canada’s Privacy Policy can be found here: Privacy Policy | BDO Canada.

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