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Added 6 mins ago
Staff Data Engineer
ExaCare AI
Toronto, Ontario
We’re looking for a Staff Data Engineer who thrives in an environment with strong ownership and can drive complex data initiatives from concept to production. You’ll build the pipelines,…
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Toronto, ON
- Contract
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Expression of Interest for Engineering Graduate - University of Calgary
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Vancouver, BC
- Full-time
…they meet today's needs and transition to more sustainable…
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Toronto, ON
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Forward Deployed Engineer – AI, Data Engineering & MLOps / Toronto, ON (Onsite) - FTE
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Added 49 mins ago
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Toronto, ON · Greater Toronto Area, Canada
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Applied AI Engineer
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Forward deployed Engineer
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- $100,000 to $120,000 CAD / year
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Forward deployed Engineer
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TELUS Digital

Robotics QA Automation Engineer

Canada

Full-time

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Job details

Job type: Full-time
Experience: Experience: 3+ years of experience in AI/ML engineering, data engineering, or workflow orchestration.
Posting language: English
Posted: Oct 9, 2026

Original job description

Robotics QA Automation Engineer

Role Description

We are looking for an innovative and detail-oriented Robotics Automation Specialist to join our team. In this role, you will work closely with Quality Specialists that have established rubrics and industry leading best practices for robotics data collection and annotation. You will be responsible for translating them into designing, integrating, and managing workflows that connect multiple AI models, tools, and services with human-in-the-loop to deliver scalable, efficient, and business-aligned solutions. The ideal candidate has strong technical expertise in AI/ML, experience with orchestration frameworks, and the ability to translate business needs into automated, AI-driven processes. This position requires a blend of engineering, problem-solving, and strategic thinking to ensure that Robotics initiatives are effectively deployed, optimized, and continuously improved.

Key Responsibilities:

Previous experience with high quality egocentric data collection and annotation pipelines from Automation and HITL perspectives
Design and implement orchestration pipelines that connect multiple GenAI models, APIs, and tools into end-to-end workflows.
Collaborate with data scientists, engineers, and business stakeholders to define use cases and translate them into orchestrated AI solutions.
Ensure system scalability, performance, and reliability through effective orchestration strategies.
Monitor and optimize AI pipelines, addressing bottlenecks, errors, and inefficiencies.
Integrate orchestration platforms with cloud environments and enterprise systems.
Establish best practices for AI orchestration, versioning, monitoring, and lifecycle management.
Document processes, technical architectures, and orchestration standards for knowledge sharing.
Stay updated on advancements in AI orchestration, LLMs, and automation tools to continuously enhance solutions.

Requirements:

Education: Bachelor’s or Master’s Degree in Computer Science, Data Engineering, Artificial Intelligence, or related field (or equivalent experience).
Experience: 3+ years of experience in AI/ML engineering, data engineering, or workflow orchestration. Experience in GenAI/LLM orchestration is a strong plus.

Skills:

Proficiency with orchestration tools/frameworks (e.g., Airflow, Prefect, LangChain, Dagster, Kubeflow, or similar).
Strong programming skills (Python preferred) for building and integrating orchestration pipelines.
Familiarity with Generative AI models (e.g., LLMs, diffusion models) and their deployment.
Knowledge of cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
Strong problem-solving and analytical skills to optimize workflows.
Excellent communication and collaboration skills to work across technical and non-technical teams.
Ability to balance innovation with reliability and compliance considerations.

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More about this job

Responsibilities

Design, integrate, and manage scalable orchestration workflows connecting AI models, APIs, tools, cloud environments, and human-in-the-loop processes for robotics data collection and annotation. Monitor and optimize pipeline performance and reliability, establish orchestration and lifecycle-management practices, and document technical standards while collaborating with technical and business stakeholders.

Requirements

A bachelor’s or master’s degree in computer science, data engineering, artificial intelligence, or a related field is required, or equivalent experience, along with at least three years of experience in AI/ML engineering, data engineering, or workflow orchestration. Candidates should have strong Python and orchestration-framework skills, familiarity with generative AI and cloud platforms, and knowledge of Docker or Kubernetes, plus strong analytical, communication, and collaboration abilities.

Skills

AI/ML Engineering
Workflow Orchestration
Python
Generative AI
LLM Orchestration
Airflow
Prefect
LangChain
Dagster
Kubeflow
Cloud Platforms
Docker
Kubernetes
Robotics Data Collection
Data Annotation
Pipeline Monitoring

Visa sponsorship

Not detected in the job text

Keywords

Robotics
Quality Assurance
Automation
Human-in-the-Loop
Egocentric Data Collection
Data Annotation
AI/ML Engineering
Workflow Orchestration
Generative AI
Large Language Models
Diffusion Models
Python
Airflow
Prefect
LangChain
Dagster
Kubeflow
APIs
Cloud Platforms
AWS
GCP
Azure
Docker
Kubernetes
Pipeline Monitoring
Versioning
Lifecycle Management
Scalability
Reliability
Data Engineering

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