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Added 2 months ago
Software Engineer, Full-Stack Applications, Associate Director (Python & React)
Fitch Group
Toronto, ON
Knowledge of MLOps practices and model deployment
Added 2 months ago
H
Data DevOps Engineer
HSBC
Toronto, ON
- Full-time
Participate in the deployment lifecycle of machine learning models and applications, including Machine Learning Operations (MLOps) and Large Language Model Operations (LLMOps) practices
Added 2 months ago
C
Senior Platform Engineering Specialist
CGI
Toronto, ON
- Full-time
…modern technology platforms that improve software delivery, developer productivity, operational resilience, security, and business…
Added 2 months ago
C
Senior Data Platform Engineering Specialist
CGI
Toronto, ON
- Full-time
Support enterprise adoption of Artificial Intelligence, MLOps, and Retrieval-Augmented Generation (RAG) capabilities by building the foundational data layers required to support them.
Added 2 months ago
H
Director, Data & AI (Hybrid)
Homebase
Toronto, ON
- $230,000 to $273,000 CAD / year
- Full-time
…recommendation systems and intelligent automation. Own the MLOps lifecycle from experimentation to…
Added 2 months ago
V
Machine Learning Engineer Lead
Vancity
Vancouver, BC · Toronto, ON
- Full-time
…lifecycle, including model development, feature engineering, MLOps, deployment automation, monitoring, and continuous improvement of machine learning systems. Success in this role is…
Added 1 month ago
VA
Member of Technical Staff - ML Operations
Veeda AI
Remote, Canada
- Full-time
- Remote
Experience in shipping production-quality developer tools.
Added 2 months ago
XR
AI Platform & Machine Learning Engineer
XYZ Reality
Remote, Canada
- Full-time
- Remote
Added 2 months ago
BS
Analyste, Habilitation & Gouvernance en IA/AI Enablement & Governance Analyst
Browns Shoes
Montreal, QC
- Full-time
Added 2 months ago
P
Back End Developer
PartsAvatar.ca
Montreal, QC
- Full-time
Added 2 months ago
A
Principal Software Engineer
Acceldata
Kitchener, ON
- Full-time
Experience with ML infrastructure, feature stores, or MLOps platforms.
Added 2 months ago
Director, AI & Data Science (Marketing Measurement & Effectiveness)
Welcome to the Jungle
Montreal, QC
Added 2 months ago
Senior Python Developer
Ampliwork
Montreal, QC
We are looking for a Senior Python Developer with strong core software engineering fundamentals and hands-on experience building production-grade, cloud-native systems.
Added 2 months ago
S
Frontend / UX Engineer - Robotics Data Operations, Kitchener, ON
Siemens
Kitchener, ON
- Full-time
UX for Technical Products: Experience designing or implementing interfaces for developer tools, data platforms, engineering workflows, AI tools, or industrial software.
Added 2 months ago
S
Agentic AI & DevOps Automation Engineer - Robotics Data Platform, Kitchener, ON
Siemens
Kitchener, ON
- Full-time
Improve Developer Experience: Create templates, tooling, documentation, and reusable automation to help engineers move faster with higher quality.
Added 2 months ago
S
Senior AI/ML & Robotics Platform Engineer
Siemens
Kitchener, ON
- Full-time
Experience with PyTorch ecosystem tooling, experiment tracking, MLOps, or evaluation pipelines.
Added 2 months ago
K
Senior Software Engineer, AI
Klue
Toronto, ON
- $140,000 to $230,000 CAD / year
- Full-time
MLOps tools: Weights & Biases, MLflow, Langfuse
Added 2 months ago
BC
AI/ML Ops Engineer
Blackpoint Cyber
Remote, Canada
- $131,000 to $164,250 CAD / year
- Full-time
- Remote
MLOps Workflows (MLFlow, Sagemaker Pipelines)
Added 2 months ago
Senior Manager AI Solutions Architecture
Diligent Corporation
Vancouver, BC
Familiarity with MLOps/LLMOps practices (model lifecycle, experiment tracking, evaluation, drift monitoring) and modern engineering practices such as containerization and CI/CD.
Added 2 months ago
TA
Lead AI Engineer
Tiger Analytics
Canada
- Full-time
The ideal candidate will combine deep expertise in AI engineering, distributed systems, cloud-native architectures, and MLOps with exceptional stakeholder management skills. This individual…
Added 2 months ago
B
AI Inference Engineer
Baseten
Montreal, QC
- $165,000 to $330,000 USD / year
- Full-time
…applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing…
Added 2 months ago
Director of AI
PureFacts Financial Solutions
Toronto, ON
Establish best practices for MLOps, model lifecycle management, and deployment pipelines, including model registries, feature stores, and retraining pipelines
Added 2 months ago
PF
AI Engineer
PureFacts Financial Solutions
Toronto, ON
- $100,000 to $120,000 CAD / year
Collaborate with MLOps to ensure scalable and maintainable deployments
Added 2 months ago
G
Analyste de données / Data Scientist
Genetec
Montreal, QC
- Full-time
Expérience dans le déploiement et la surveillance de modèles d'apprentissage automatique en production (MLOps)
Added 2 months ago
GD
Data Scientist I
Groupe Dynamite
Mont-Royal, QC
- Full-time
You are an experienced cloud developer with a passion for data science and data modeling.

HSBC

Data DevOps Engineer

Toronto, ON, Canada

Full-time

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Job details

Job type: Full-time
Posting language: English
Posted: Aug 19, 2026

Original job description

Our purpose – Opening up a world of opportunity – explains why we exist. Here at HSBC, we use our unique expertise, capabilities, breadth and perspectives to open new kinds of opportunity for our more than 40 million customers. We’re bringing together the people, ideas, and capital that nurture progress and growth, helping to create a better world – for our customers, our people, our investors, our communities, and the planet we all share.

In Canada, HSBC Global Services (Canada) Limited (HGCA) is a wholly owned subsidiary of HSBC Global Services Limited. Operating in Toronto and Vancouver, HGCA is part of a global service company, delivering services to support the operating entities of HSBC Group. We have different capabilities that provide tools and processes to facilitate the functions, business, and entities with their service management responsibilities.

Chief Technology Office (CTO) Data Technology is a data-driven shared service organization committed to unlocking value from data to serve our customers. We are a unified data technology team with a diverse organization of more than 3,000 colleagues across multiple global locations. We are transforming data technology into an Enterprise Shared Service Capability delivery model that will scale across key Global and Regional business markets.

Our CTO Analytics Technology team is at the forefront of developing cutting-edge data science platforms across multi-cloud environments. We leverage advanced analytics and data-driven insights to enhance our services and drive business growth.

We are looking for a passionate and driven Data Development and Operations (Data DevOps) Engineer to join our CTO Analytics Technology team. In this role, you will work on a state-of-the-art data science platform, collaborating with data engineers, data scientists, and other stakeholders to optimize data workflows and enhance our analytics capabilities across multi-cloud environments.

As our Data DevOps Engineer you will:

Assist in the development, deployment, and maintenance of data pipelines and workflows using Big Data technologies such as Apache Hadoop (Hadoop), Hadoop Distributed File System (HDFS), Google BigQuery (BigQuery), Amazon EMR (EMR), Snowflake, and Databricks
Support data science initiatives by utilizing tools such as JupyterHub, MLflow, Google Vertex AI (Vertex AI), Google Cloud Dataproc (Dataproc), Google Cloud Dataflow (Dataflow), and Apache Airflow (Airflow)
Collaborate with data scientists to implement machine learning models and workflows using libraries such as TensorFlow and scikit-learn
Utilize data manipulation libraries such as pandas, NumPy, and PySpark for data analysis and processing
Develop and maintain Python 3 (Python) applications and Application Programming Interfaces (APIs) to support data workflows and analytics
Monitor and troubleshoot data pipelines to ensure data quality and reliability
Participate in the deployment lifecycle of machine learning models and applications, including Machine Learning Operations (MLOps) and Large Language Model Operations (LLMOps) practices
Work with container orchestration tools such as Kubernetes (K8s) to manage and deploy applications in cloud environments
Stay updated with the latest trends and technologies in data engineering, DevOps, and cloud computing

You’ll likely have the following qualifications to succeed in this role:

Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field (or equivalent practical experience)
Familiarity with Big Data technologies (Hadoop, HDFS, BigQuery, EMR, Snowflake, Databricks)
Experience with data science tools (JupyterHub, MLflow, Vertex AI, Dataproc, Dataflow, Airflow)
Experience with data manipulation libraries (pandas, NumPy, PySpark)
Proficiency in Python, including experience in building APIs and applications
Familiarity with cloud platforms such as Google Cloud Platform (GCP), Amazon Web Services (AWS), and Microsoft Azure (Azure), and their services
Basic knowledge of Linux operating systems
Understanding of Kubernetes (K8s), MLOps/LLMOps, and experience with Large Language Models (LLMs) such as OpenAI, Claude, or Gemini (preferred)

In compliance with applicable laws, HSBC is committed to employing only those who are authorized to work in Canada. Applicants must be legally authorized to work in Canada as HSBC will not engage in immigration sponsorship for this position.

As an HSBC employee, you will have access to tailored professional development opportunities to ensure you have the right skills for today and tomorrow. At HSBC, our overall goal is to provide a competitive Total Reward Package, with an appropriate mix of fixed pay, and variable pay, as part of an employee’s overall total compensation and benefits. Variable pay generally takes the form of discretionary, annual awards (sometimes referred to as a “bonus”). Additionally, HSBC offers a wide range of competitive and flexible benefits designed to help you improve your health and well-being, finances, and lifestyle.

All qualified applicants will receive consideration for employment without regard to age, ancestry, color, race, national origin, ethnicity, disability or medical condition, genetic information, military or veteran service, religion, creed, sex, gender, pregnancy, childbirth, caregiver status, marital status, citizenship or immigration status, sexual orientation, gender identity or expression or any other trait protected by applicable law.

The final fixed pay offer will depend on the candidate and a number of variables, including but not limited to, role responsibilities, skill set, depth of experience and education, licensing/certification requirements, internal relativity, and specific work location.

At HSBC, our overall goal is to provide a competitive Total Reward Package, with an appropriate mix of fixed pay, and variable pay, as part of an employee’s overall total compensation and benefits. Variable pay generally takes the form of discretionary, annual awards (sometimes referred to as a “bonus”). Additionally, HSBC offers a wide range of competitive and flexible benefits designed to help you improve your health and well-being, finances, and lifestyle.

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More about this job

Responsibilities

The Data DevOps Engineer will develop, deploy, and maintain data pipelines and workflows using Big Data technologies while collaborating with data scientists to implement machine learning models. They will also monitor and troubleshoot data systems to ensure quality and reliability across multi-cloud environments.

Requirements

Candidates must hold a bachelor's degree in Computer Science, Data Science, Engineering, or a related field. Proficiency in Python, experience with Big Data technologies, and familiarity with cloud platforms and Kubernetes are required.

Skills

Python
Apache Hadoop
Google BigQuery
Snowflake
Databricks
Kubernetes
MLOps
LLMOps
Apache Airflow
PySpark
TensorFlow
Scikit-learn
Data pipelines
Cloud computing
Data engineering
API development

Benefits

Professional development opportunities
Competitive total reward package
Health and well-being benefits
Flexible benefits

Visa sponsorship

Not detected in the job text

Keywords

Data DevOps
Big Data
Hadoop
HDFS
BigQuery
EMR
Snowflake
Databricks
JupyterHub
MLflow
Vertex AI
Dataproc
Dataflow
Airflow
TensorFlow
Scikit-learn
Pandas
NumPy
PySpark
Python
APIs
MLOps
LLMOps
Kubernetes
Cloud Computing
GCP
AWS
Azure
Linux
Large Language Models

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