Technical Consultant – Machine Learning

Posted 13 Days Ago
Be an Early Applicant
Hiring Remotely in Office, Machaze, Manica, MOZ
Remote
30K-70K Annually
Senior level
Software • Financial Services
The Role
As a Machine Learning Engineer, design, deploy, and maintain scalable ML solutions, optimize infrastructure, and collaborate with stakeholders across teams to improve business decisions and operational efficiency.
Summary Generated by Built In
About the OpportunityJob Type: Permanent

Application Deadline: 30 June 2026

Job Description

                                                                                                

Title                 Techcnial Consultant – Machine Learning

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

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.
  • Familiarity with MLOps practices, model versioning, and monitoring.
  • Solid problem-solving skills with strong attention to detail.
  • Excellent communication and cross-functional collaboration skills.
Nice to Have
  • Ability to write efficient SQL queries for cloud-based data warehouses such as Snowflake or Amazon Redshift.
  • Experience developing ML-driven applications within the mutual fund, asset management, or investment management industry.
     

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.

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The Company
HQ: London
9,919 Employees
Year Founded: 1969

What We Do

Fidelity International offers investment solutions and services and retirement expertise to more than 2.5 million customers globally. As a privately held, purpose-driven company with a 50-year heritage, we think generationally and invest for the long term. Operating in more than 25 countries and with $739.9 billion* in total assets, our clients range from central banks, sovereign wealth funds, large corporates, financial institutions, insurers and wealth managers, to private individuals. Our Workplace & Personal Financial Health business provides individuals, advisers and employers with access to world-class investment choices, third-party solutions, administration services and pension guidance. Together with our Investment Solutions & Services business, we invest $567 billion on behalf of our clients. By combining our asset management expertise with our solutions for workplace and personal investing, we work together to build better financial futures. *Data as of 31 March 2021

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