Publié il y a 3 mois
AI Modeling Engineer
@ Palona AI
Toronto, Ontario
En bref
Palona AI is hiring an applied AI Modeling Engineer to improve the intelligence, accuracy, safety, latency and cost of its voice and multimodal restaurant agents. The role covers model selection, prompting, fine-tuning, evaluation and production feedback. The posting states a full-time employment type and a competitive salary with stock options.
Responsabilités :
- Develop modeling and experimentation strategies for voice and language agents
- Build offline and online evaluations and representative datasets
- Evaluate frontier and open-source models and make build or fine-tune decisions
- Ship model changes with guardrails, staged rollouts and monitoring
Résumé des exigences :
- 3+ years of industrial experience in a relevant technical domain
- Strong machine learning foundations and production AI experience
- Strong Python and modern ML tooling such as PyTorch or JAX
- Practical experience with LLMs, speech, multimodal or agentic systems
Outils et compétences
Avantages mentionnés
Source et dates
Site carrière / système de candidatures · workable
- Date publiée par l’employeur
- 2026-08-10
- Première détection par notre source
- 2026-10-09
- Mise à jour du dossier source
- 2026-10-09
Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.
Détails du poste
| Niveau | Intermédiaire |
| Domaine | Développement logiciel |
| Expérience | 3 an(s) et plus |
| Heures par semaine | 40 (estimé) |
| Milieu de travail | Bureau |
| Position | Surtout assis |
| Exigences physiques | physique faible · ordinateur élevé |
| Langues | English |
Résumé et détails rédigés par l’IA à partir de l’offre; l’offre de l’employeur fait foi.
Palona AI
Profil d’entreprise sauvegardé
Renseignements historiques provenant d’un profil The Jobs API sauvegardé (champs LinkedIn/Crunchbase). Ils ne sont pas vérifiés en temps réel; les chiffres peuvent avoir changé. Les valeurs manquantes restent inconnues.
Bring your brand to life. Make your customers fall in love.
Description complète de l’entreprise
We are building a new, completely proprietary AI system with multi-agents, multimodal-to-action models, combined with unrivaled emotional intelligence language models to empower businesses to scale by delivering a high-touch customer experience, automation and efficiency. Our AI Agents will supercharge the core of your business.
- Abonnés LinkedIn
- 3 005
- Personnes associées sur LinkedIn
- 31
- Bureaux déclarés
- Menlo Park, CA 94025, US
- Catégories d’activité
- Brand Marketing
- Software
- Artificial Intelligence (AI)
- Autres noms enregistrés
- Palona AI
- Le profil indique une agence de recrutement
- Non
- Investissement total déclaré
- 10 000 000
La devise et la date d’observation ne sont pas fournies; ce n’est ni une valorisation actuelle ni une ronde de financement.
We are building a new, completely proprietary AI system with multi-agents, multimodal-to-action models, combined with unrivaled emotional intelligence language models to empower businesses to scale by delivering a high-touch customer experience, automation and efficiency. Our AI Agents will supercharge the core of your business.
| Champ | Valeur |
|---|---|
| Secteur | Software Development |
| Taille | 11-50 employees |
| Siège social | Menlo Park, CA |
| Type d’organisation | Privately Held |
| Fondée en | 2024 |
| Offres sur Jobsy | 5 |
| Voir la page |
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.
Journal
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