About the Opportunity

Job Type: Permanent

Application Deadline: 30 June 2026

• Job Description

                                                                                                  

  Title                 Techcnial Consultant – Machine Learning DevOps

  Department      Enterprise Service-Canada Delivery

  Location          Dalian

  Reports To       Technical Manager

  Level                5

  We’re proud to have been helping our clients build better financial futures for over 50 years. How have we achieved this? By working together - and supporting each other - all over the world. So, join our team and feel like you’re part of something bigger.

  About your team

  The technology service team provides IT services to the Fidelity International business, globally. These include the development and support of business applications that underpin our revenue, operational, compliance, finance, legal, and marketing and customer service functions. 

  About your role
  As a Machine Learning Engineer at Fidelity Investments Canada, you will design, build, deploy, and maintain scalable machine learning solutions that enables business units to make informed decisions, improve operational efficiency, and drive growth. This role requires close collaboration with stakeholders across Data Science, Analytics, Architecture, and Agile delivery teams.

  About you

  Fast learning and strong logical thinking, the successful candidate for this position is expect to contribute in below areas:

• Design, develop, deploy, and maintain end-to-end machine learning models and pipelines in production environments.
• Design and maintain robust Data pipelines to support the seamless flow of data from source systems to machine learning platforms.
• Build scalable feature engineering, model training, and inference workflows.
• Deploy batch and real-time ML solutions into AWS cloud-based environments.
• Implement model lifecycle management practices including versioning, testing, monitoring, and retraining strategies.
• Develop CI/CD pipelines for ML workflows to ensure reproducibility and reliability.
• Monitor model performance, drift, bias, and stability in production.
• Ensure ML solutions comply with financial industry governance, model risk Management (MRM), and regulatory standards.
• Collaborate with risk and compliance teams to support validation, auditability, and documentation requirements.
• Optimize infrastructure for scalability, performance, and cost efficiency.
• Work with enterprise data platforms and cloud-based data warehouses.

• Required Skills & Qualifications

  Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field.
• 5 years of hands-on experience building and deploying machine learning solutions in production.
• Experience working in cloud environments (AWS, GCP, or Azure).
• Hands-on experience with AWS SageMaker and/or Google Vertex AI.
• Experience working within regulated environments (financial services preferred).

• Technical Skills & Expertise

• Strong proficiency in Python and experience with machine learning frameworks such as TensorFlow and PyTorch.
• Strong understanding of machine learning concepts, algorithms, LLMs, and modern ML frameworks.
• Experience implementing end-to-end ML pipelines including data preparation, training, validation, and deployment using cloud ML Services like AWS Sagemaker or Google Vertex AI.
• Experience with containerization and orchestration (Docker, Kubernetes).
• Familiarity with MLOps practices, model versioning, and monitoring.
• Solid problem-solving skills with strong attention to detail.
• Excellent communication and cross-functional collaboration skills.
• Good business English skill is required, reading, writing, listening, speaking
   

• Feel rewarded

  For starters, we’ll offer you a comprehensive benefits package. We’ll value your wellbeing and support your development. And we’ll be as flexible as we can about where and when you work – finding a balance that works for all of us. It’s all part of our commitment to making you feel motivated by the work you do and happy to be part of our team. For more about our work, our approach to dynamic working and how you could build your future here, visit careers.fidelityinternational.com.

  For more about our work, our approach to dynamic working and how you could build your future here, visit careers.fidelityinternational.com.

• Contribute to the enhancement of internal ML platforms, tooling, and engineering best practices.