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Added 4 days ago
A(
Machine Learning Resident - Client: Trufla (12 month term)
Amii (Alberta Machine Intelligence Institute)
AB · Edmonton, AB
- Full-time
…tomorrow's insurance ecosystem. If you are an AI/ML researcher or engineer looking to apply your skills to address high-stake business problems with strict liability constraints, we want to…
Added 5 days ago
Senior Applied AI Engineer - Artificial Intelligence
Bloomberg
Toronto, ON
…over structured data. They bridge the gap between pioneering research and production, building models and agents that answer complex financial questions, write and execute code, and bring…
Added 1 month ago
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Senior Machine Learning Systems Engineer (CAD)
PointClickCare
Mississauga, ON
- Full-time
With the largest long-term and post-acute care dataset and a Marketplace of 400+ integrated partners, our platform serves over 30,000 provider organizations, making a real difference in…
Added 1 month ago
P
Senior Machine Learning Systems Engineer (CAD)
PointClickCare
Mississauga, ON
- $154,000 to $193,000 CAD / year
- Full-time
With the largest long-term and post-acute care dataset and a Marketplace of 400+ integrated partners, our platform serves over 30,000 provider organizations, making a real difference in…
Added 1 month ago
K
Machine Learning Data Engineer
kadence
Montreal, QC
- Full-time
If you’ve worked on LLM training data, large-scale NLP pipelines, foundation-model infrastructure or web-scale data processing, I’d be interested in speaking with you.
Added 2 months ago
P
Principal AI Engineer
PointClickCare
Mississauga, ON
- Full-time
With the largest long-term and post-acute care dataset and a Marketplace of 400+ integrated partners, our platform serves over 30,000 provider organizations, making a real difference in…
Added 2 months ago
PA
AI Modeling Engineer
Palona AI
Toronto, ON
- Full-time
We are looking for an applied AI Modeling Engineer to improve the intelligence, accuracy, safety, latency, and cost of Palona's voice and multimodal agents. You will own problems across…
Added 1 month ago
Machine Learning Engineer, Safety and Customer Care AI
Lyft
Toronto, ON
As a Machine Learning Engineer on the SCC team, you will fine-tune and align models and build AI Agents that power how riders and drivers get help. Your work spans the full loop:…
Added 3 months ago
E
Staff Machine Learning Engineer
EvenUp
Toronto, Ontario
- $212,000 to $301,000 USD / year
- Full-time
Drive data excellence through hands-on analysis of training and evaluation data, managing noise, edge cases, and drift at scale.

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Palona AI

AI Modeling Engineer

Toronto, ON, Canada

Full-time

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Job details

Job type: Full-time
Apply by: Feb 7, 2027
Experience: 3+ years of industrial experience in relevant technical domain
Posting language: English
Posted: Aug 11, 2026

Original job description

Palona's AI agents operate in real restaurant environments: noisy phone lines, varied accents, complex menus, interruptions, incomplete information, strict business rules, and customers who expect an immediate, natural response. Improving these systems requires more than selecting the newest model. It requires disciplined evaluation, high-quality data, modeling judgment, experimentation, and production feedback loops.

We are looking for an applied AI Modeling Engineer to improve the intelligence, accuracy, safety, latency, and cost of Palona's voice and multimodal agents. You will own problems across model selection and routing, prompting and context, fine-tuning or post-training when justified, speech and language quality, evaluation methodology, dataset development, and model behavior in production.

This is a product-facing modeling role. Research depth matters, but success is measured by improvements that survive contact with production and create better guest, restaurant, and business outcomes. You will work closely with product, full-stack, infrastructure, and customer-facing engineers to move from hypothesis to experiment to reliable deployment.

What You'll Own

Develop modeling and experimentation strategies for high-impact agent problems in voice, language, reasoning, ordering, multilingual behavior, and multimodal understanding
Build rigorous offline and online evaluations that measure task completion, accuracy, safety, latency, cost, conversational quality, and business outcomes
Create and maintain representative datasets from simulations, human annotation, production feedback, and difficult edge cases while protecting sensitive data
Evaluate frontier and open-source models and make clear build, buy, route, prompt, fine-tune, or distill decisions
Improve prompting, context construction, memory, tool-use policies, structured outputs, model routing, and fallback behavior
Design fine-tuning, preference optimization, distillation, or other post-training work when it offers a measurable advantage over simpler methods
Partner with speech and real-time engineers to improve ASR, TTS, turn-taking, interruption handling, pronunciation, multilingual behavior, and end-to-end latency
Develop analysis tools that explain model failures, slice performance by scenario, detect regressions, and accelerate iteration
Ship model changes with production guardrails, staged rollouts, monitoring, rollback paths, and clear quality gates
Translate new research and model releases into concrete product opportunities and communicate tradeoffs to technical and non-technical partners
Raise scientific and engineering standards through reproducible experiments, thoughtful reviews, and clear documentation

Requirements

3+ years of industrial experience in relevant technical domain
Strong machine learning foundations and hands-on experience developing or evaluating production AI systems
Strong Python skills and experience with modern ML tooling such as PyTorch, JAX, Hugging Face, or equivalent systems
Practical experience with LLMs, speech models, multimodal models, or agentic systems
Ability to design reliable experiments, define useful metrics, analyze noisy results, and avoid optimizing against weak proxies
Experience building datasets, evaluation harnesses, model services, or training and inference pipelines
Strong software engineering judgment; your work is reproducible, tested, observable, and usable by other engineers
Ability to connect modeling choices to product constraints including latency, cost, privacy, safety, and user experience
Comfort operating in ambiguity and collaborating across research, engineering, product, and customer contexts
AI-native working habits and genuine curiosity about new model capabilities and limitations

Benefits

Competitive Salary and Stock Option Plan
Medical, dental, vision, retirement, leave, and disability benefits as applicable
Family Leave
Short Term & Long Term Disability
Paid time off and company holidays
Learning and development support

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More about this job

Responsibilities

Develop and optimize modeling strategies for voice and multimodal AI agents to improve intelligence, accuracy, and latency. Build rigorous evaluation frameworks and datasets to measure task completion and business outcomes in production environments.

Requirements

Requires over 3 years of industrial experience in machine learning with strong Python skills and proficiency in tools like PyTorch or Hugging Face. Candidates must have practical experience with LLMs or agentic systems and the ability to connect modeling choices to product constraints.

Skills

Python
PyTorch
JAX
Hugging Face
Large Language Models
Fine-tuning
Prompt Engineering
Model Evaluation
Speech Models
Multimodal Models
Dataset Development
Machine Learning
Software Engineering
ASR
TTS
Model Distillation

Benefits

Competitive Salary
Stock Option Plan
Medical Insurance
Dental Insurance
Vision Insurance
Retirement Benefits
Leave Benefits
Disability Benefits
Family Leave
Short Term Disability
Long Term Disability
Paid Time Off
Company Holidays
Learning And Development Support

Visa sponsorship

Not detected in the job text

Keywords

AI Modeling
LLM
Voice Agents
Multimodal AI
PyTorch
JAX
Hugging Face
ASR
TTS
Fine-tuning
Preference Optimization
Distillation
Model Routing
Prompting
Dataset Development
Evaluation Harness
Inference Pipelines
Latency Optimization
Machine Learning
Software Engineering
Agentic Systems
Multilingual Behavior
Production Guardrails
Model Monitoring
Python

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