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Ai In Jobs in Toronto, ON (NOW HIRING)

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 ...

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 ...

We are looking for a product-focused AI Software Engineer to turn advances in AI into restaurant products that work reliably in the real world. You will build across customer-facing experiences ...

We are looking for a product-focused AI Software Engineer to turn advances in AI into restaurant products that work reliably in the real world. You will build across customer-facing experiences ...

Requirements * 3+ years of industrial experience in relevant technical domain. * Strong full-stack ... AI-native working habits and a practical view of where automation needs human judgment. * Comfort ...

Requirements * 3+ years of industrial experience in relevant technical domain. * Strong full-stack ... AI-native working habits and a practical view of where automation needs human judgment. * Comfort ...

Account Executive

Toronto, ON · Remote

CA$60K - CA$65K/yr

We do not use AI in our recruitment process. About our Client: They make studio-quality, identity-ready headshots accessible anywhere by pairing premium self-serve capture with a secure platform that ...

Account Executive

Toronto, ON · Remote

CA$60K - CA$65K/yr

We do not use AI in our recruitment process. About our Client: They make studio-quality, identity-ready headshots accessible anywhere by pairing premium self-serve capture with a secure platform that ...

Showing results 41-60

Ai In information

What is the difference between Ai In vs Data Analyst?

AspectAi InData Analyst
Required CredentialsTypically a degree in AI, computer science, or related field; certifications in AI or machine learningDegree in statistics, mathematics, or related field; certifications in data analysis or visualization
Work EnvironmentTech companies, AI research labs, startups; focus on developing AI modelsBusiness, finance, healthcare sectors; analyze data to inform decisions
Employer & Industry UsagePrimarily in tech and AI-focused industriesAcross various industries including finance, healthcare, marketing

While both roles involve working with data, Ai In focuses on developing and implementing AI models, whereas Data Analysts interpret data to support business decisions. Ai In roles require specialized knowledge in AI and machine learning, while Data Analysts focus on data visualization and statistical analysis.

What cities near Toronto, ON are hiring for Ai In jobs?

Cities near Toronto, ON with the most Ai In job openings:

Infographic showing various Ai In job openings in Toronto, ON as of August 2026, with employment types broken down into 71% Full Time, 26% Part Time, and 3% Contract. Highlights an 67% Physical, 4% Hybrid, and 29% Remote job distribution.

AI Modeling Engineer

Palona AI

Toronto, ON • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 5 days ago


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.