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Added 48 mins ago
M
Senior Full Stack Software Engineer - Capital Markets
Manulife
Toronto, ON
- Full-time
We're seeking a Senior Full-Stack Engineer with strong software engineering expertise and experience in derivatives trading systems. In this role, you'll design, develop, and support…
Added 48 mins ago
M
Agentic Engineer, Innovation
Manulife
Montreal, QC
- Full-time
Strong Python and SQL skills, with experience in AI application architecture, orchestration, retrieval, prompt design, evaluation, integration, and production monitoring.
Added 48 mins ago
GM
2027 Winter Co-op Data Engineering Software Developer
General Motors
Markham, ON · Oshawa, ON
- Full-time
Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to Markham Elevation Centre (MEC) or Oshawa Elevation Centre (OEC) three times per week…
Added 1 hour ago
M
Senior Cloud Infrastructure Engineer
Mecka
Remote, Canada
- $165,000 to $200,000 CAD / year
- Full-time
- Remote
…builds and runs. We're hiring a Senior Cloud Infrastructure Engineer to help design, scale, and harden Mecka's AWS environment, with a focus on the networking and storage behind global data…
Added 5 hours ago
M
Data Engineer
Manulife
Toronto, ON · Waterloo, ON
- Full-time
As a Data Engineer at Manulife, you would play a critical role in the development and maintenance of the company's data systems and architecture. You would collaborate with other highly…
Added 7 hours ago
A
Test Engineer
Actalent
Quebec, QC
- $40 to $58 CAD / hour
- Contract
Il s'agit d'un poste hybrid, situé à Quebec,QC.
Added 7 hours ago
A
Software Engineer
Actalent
Ottawa, ON
- $50 to $74 CAD / hour
- Contract
Experience with Python scripting at a mid level, particularly for automation and testing.
Added 7 hours ago
A
Cloud Software Engineer
Actalent
Ottawa, ON · Kanata, ON
- $46 to $65 CAD / hour
- Contract
This position is based in Kanata, Ontario and requires a hybrid work arrangement with four days onsite per week at the Ottawa Engineering Center.
Added 8 hours ago
C
Lead Threat Intelligence Engineer
CapitalG
Toronto, ON
- Full-time
You will work closely with Clio's internal red team and detection engineer. Threat Intelligence characterizes the adversary - who they are, how they operate, what to watch for. The Red Team…
Added 9 hours ago
CS
Senior Research Engineer - Inference ML
Cerebras Systems
Canada
- Full-time
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750…
Added 9 hours ago
GD
Co-op Winter 2027 - Software Developer - 8 Months
General Dynamics Missions System International
Ottawa, ON
- Internship
The Applications team for the Land C5ISR Program is looking for a Co-op Software Engineer to join our team. We develop and integrate various software products that enable the Canadian Army…
Added 10 hours ago
M
Winter Co-op 2027 – Automation Engineer (12 months)
Manulife
Toronto, ON · Waterloo, ON
- Full-time
As an Automation Engineer Co-op, you'll help identify opportunities to simplify, streamline, and automate business and operational processes across the organization. Working closely with…
Added 10 hours ago
T
Sr. Engineer, Systems Debug
Tenstorrent
Toronto, ON
- Full-time
An engineer with strong post-silicon validation and bring-up experience who is comfortable working in the lab and getting deep into system-level behavior.
Added 10 hours ago
Infrastructure Software Engineer
CCLIM - Quantitative Equity
Vancouver, BC
The technology infrastructure team plays an essential role through innovative technologies on our hybrid (on-premise and cloud based) platform: distributed computing, petabyte-scale data…
Added 11 hours ago
C
Backend Engineer
Creator.co
Vancouver, BC
- Full-time
Experience supporting or working with Python-based microservices or data layers.
Added 12 hours ago
AI
JAMS Platform Engineer
Apptoza Inc.
Toronto, ON
- Contract
Seeking a hands-on engineer to drive the reliability| automation and modernization of the enterprise JAMS workload automation platform. The role combines JAMS platform expertise with…
Added 12 hours ago
1P
Artificial Intelligence Engineer
10 Percent Recruiting Ltd.
AB · Greater Edmonton Metropolitan Area
- Contract
Partner with the Data Engineer to support vector search, semantic search, and enterprise knowledge repositories.
Added 12 hours ago
CT
Principal Systems Engineer - Optical Transceivers
ConsultNet Technology Services and Solutions
Ottawa, ON
- Other
…direct search, and managed services onshore, nearshore, and hybrid. For over 25 years, we have connected thousands of consultants with meaningful roles through a personal,…
Added 13 hours ago
T
Senior Data Engineer
TriMech
Oakville, ON
- Full-time
As Senior Data Engineer / Data Scientist, you will design, build, and operate the group's data ecosystem: integrating data from our core business systems, developing robust pipelines,…
Added 13 hours ago
A
Software Engineer
Actalent
Ottawa, ON
- $50 to $74 CAD / hour
- Contract
Experience with Python scripting at a mid level, particularly for automation and testing.
Added 13 hours ago
E
Senior AI Engineer / AI Agent Lead
Emplia
Montreal, QC
- Full-time
Experience with vector databases, embeddings, semantic search, and/or hybrid search
Added 13 hours ago
Industrial Edge Integration Engineer - Physical AI hub, Kitchener
Siemens
Kitchener, ON
We are seeking an Industrial Edge Integration Engineer to help integrate the Physical AI Runtime with SIMATIC AX and Siemens Industrial Edge. SIMATIC AX is Siemens' software-defined…
Added 13 hours ago
C
Data Engineer
Citylitics
Remote, Canada
- Full-time
- Remote
…reliable sales intelligence. The platform integrates seamlessly with CRMs, ERPs, and data lakes, embedding actionable insights directly into sales workflows so teams can prioritize the…
Added 14 hours ago
FI
Software Engineer - New Grad (2026-2027)
Fellow Insights Inc.
Remote, Canada
- Full-time
- Remote
…concept to production in days, not months. You'll work directly with Product and Design, and you'll use AI tools like Cursor and Claude to ship faster while raising the quality bar. You'll…
Added 14 hours ago
CI
Data Engineer
Citylitics Inc.
Toronto, ON
- $70,000 to $80,000 CAD / year
- Full-time
…reliable sales intelligence. The platform integrates seamlessly with CRMs, ERPs, and data lakes, embedding actionable insights directly into sales workflows so teams can prioritize the…

Direct IT Recruiting Inc.

MLOps Engineer – Databricks (1896) $90-100hr

Toronto, ON, Canada

$90 to $100 CAD / hour · Contract

Apply About employer

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Job details

Pay: $90 to $100 CAD / hour
Job type: Contract
Apply by: Nov 1, 2026
Posting language: English
Posted: Oct 2, 2026

Original job description

Location: Toronto, Ontario (Hybrid – 3 days/week onsite)

Contract Duration: 14 months, 40-hour work week

Skills: Python, MLOps, LLMOps, Azure Databricks, NIST AI RMF, MLFlow, RAG, AI governance, GitHub Actions, Terraform, Jenkins

Rate: $90-100/hr

Industry: Bank

DESCRIPTION

Applied Intelligence is scaling enterprise AI across Microsoft Foundry, Databricks, Copilot Studio, and a mixed model estate spanning Anthropic, Azure OpenAI, other frontier models, and open source models.

This hands-on engineering role partners with AI Governance and Risk to translate NIST AI RMF and enterprise requirements into practical platform controls, reusable patterns, automated guardrails, and governance evidence across the AI lifecycle.

You'll join the Applied Intelligence Platforms team and work closely with Platform Engineering, Data Engineering, Enterprise Architecture, Privacy, Enterprise Security, AI Governance and Risk, and the AI Centre of Excellence. You will report to the Senior Manager, Applied Intelligence Platforms.

Apply safe deployment practices including automated builds, artifact versioning, deployment gates, and rollback strategies such as blue/green, canary, and shadow, avoiding manual production changes.
Develop operational runbooks, support procedures, incident response guidance, and recovery processes.

Responsible AI, Privacy and Governance Enablement

Partner with AI Governance, Privacy, Information Security, and the AI Centre of Excellence to translate enterprise requirements into practical implementation patterns.
Implement technical guardrails supporting responsible AI outcomes, including content safety, grounding, human-in-the-loop checkpoints, and auditability.
Apply secure AI implementation patterns aligned with OWASP guidance for LLM and agentic systems, mitigating risks such as prompt injection, insecure tool usage, model exfiltration, and data leakage.
Implement authentication and authorization flows using OAuth2 and OIDC so AI agents and services inherit appropriate user context and role-based access.
Implement privacy-supporting controls in AI solutions, such as data minimization, access scoping, retention alignment, and handling of sensitive data in prompts, logs, and retrieval sources.

AI delivery model

Define and operationalize the AI delivery model, including reusable implementation patterns, reference solutions, and engineering standards for RAG, agentic, and machine learning solutions.
Select and integrate models across the estate based on suitability, performance, and cost.
Partner with delivery teams to accelerate build and support production readiness.

MLOps, LLMOps and evaluation

Build and maintain pipelines covering development, evaluation, deployment, monitoring, and model lifecycle management.
Establish evaluation frameworks with measurable quality criteria, behavioural regression testing, and continuous evaluation of probabilistic systems.
Implement lineage, experiment tracking, and reproducibility using tools such as MLflow.

AI governance technical implementation

Translate NIST AI RMF and enterprise AI governance requirements into technical controls across Govern, Map, Measure, and Manage.
Implement reusable guardrails through platform configuration, CI/CD/IaC, evaluation gates, access controls, policy enforcement, and OWASP-aligned secure AI patterns.
Establish traceable governance evidence for models, agents, deployments, evaluations, approvals, and human-in-the-loop controls.
Partner with AI Governance and Risk to validate control effectiveness and escalate policy, privacy, security, and risk-acceptance decisions to accountable teams.

Operations, reliability and cost

Own the reliability, observability, and production support of enterprise AI services.
Own cost tracking, attribution, and optimization, treating cost as a measurable engineering metric.
Apply safe deployment practices and maintain runbooks, incident response, and recovery processes.
Enablement
Onboard teams onto approved AI platforms and patterns, and provide technical mentorship, documentation, and reusable assets.

Decision making

Independent analysis approach based on business context

What you'll need:

Qualifications:

Has shipped and supported production systems, and designs for failure.
Has debugged performance or latency issues in distributed systems.
Writes modular, testable code and favours automation over manual intervention.
Defines measurable success criteria before building, and can test systems where outputs vary.
Treats cost as a measurable engineering metric.
Bachelor's degree in a related technical field, or equivalent practical experience.

Knowledge:

Generative AI, LLMs, RAG, agentic systems, and enterprise AI application patterns.
Microsoft Foundry, Databricks/Unity Catalog/MLflow, Copilot Studio, AI Gateway/model access patterns, and mixed-model tradeoffs.
MLOps/LLMOps, CI/CD, Infrastructure as Code, evaluation, observability, and cloud-native engineering.
NIST AI Risk Management Framework (Govern, Map, Measure, Manage) and translation into engineering controls.
Responsible AI, human-in-the-loop design, auditability, privacy, IP, security, bias, and model misuse risks.
Cloud fundamentals, distributed systems and API design, observability, and data literacy.
Cloud cost management, consumption tracking, and cost attribution.
Proficiency in Python.

REQUIREMENTS

Hands-on Python coding, AI, machine learning, platform, or cloud engineering.
Hands-on experience building and operating production AI or machine learning solutions.
Experience implementing RAG and agent-based solutions.
Experience implementing MLOps and LLMOps capabilities end-to-end.
Experience implementing automated AI governance controls or evidence, ideally mapped to NIST AI RMF or another recognized framework.
Experience owning cost tracking and optimization of cloud or AI workloads.
Experience in a regulated environment is an asset.
Experience collaborating with Enterprise Architecture, Platform Engineering, Privacy, Security, and Governance teams in a large organization.
Experience in financial services, pension, asset management, or another regulated environment is an asset.

NOTE: As part of our hiring process, we use AI-based systems to support the initial screening of applicants.

To Apply: https://directitrecruiting.com/job/mlops-eng-databricks-1896/

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More about this job

Responsibilities

Build and operate production AI and machine learning platforms, pipelines, evaluation frameworks, and deployment controls, including reusable patterns for RAG and agentic systems. Implement governance, privacy, security, reliability, observability, and cost controls across the AI lifecycle, while supporting teams with onboarding, documentation, and technical mentorship.

Requirements

Candidates need hands-on Python experience and a track record building and supporting production AI or machine learning solutions, including RAG, agent-based systems, and end-to-end MLOps/LLMOps. They should be experienced with automated governance controls, cloud cost optimization, and cross-functional work in large organizations; regulated-industry experience is an asset, and a related bachelor's degree or equivalent practical experience is accepted.

Skills

Python
MLOps
LLMOps
Azure Databricks
NIST AI Risk Management Framework
MLflow
Retrieval-Augmented Generation
AI Governance
GitHub Actions
Terraform
Jenkins
Responsible AI
CI/CD
Infrastructure as Code
OAuth2
OIDC

Visa sponsorship

Not detected in the job text

Keywords

Python
MLOps
LLMOps
Azure Databricks
Microsoft Foundry
Copilot Studio
MLflow
Unity Catalog
NIST AI Risk Management Framework
Retrieval-Augmented Generation
Agentic Systems
Generative AI
Large Language Models
AI Governance
Responsible AI
GitHub Actions
Terraform
Jenkins
CI/CD
Infrastructure as Code
OAuth2
OIDC
Model Evaluation
Observability
Cloud Cost Management
Human-in-the-Loop
Privacy
OWASP
Distributed Systems
Financial Services

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