Publié il y a 1 heure
Senior Machine Learning Developer
@ Clera
Montréal, Québec
Résumé des exigences :
- Develop agent memory, knowledge graph, and customization tools to help systems adapt to different workflows.
- At least 6 years of software or machine learning engineering experience, including a track record of shipping and operating ML or LLM systems in production.
- Experience building conversational AI for phone or SMS, or related real-time and streaming systems such as voice, SIP, or WebRTC.
- Hands-on experience training and deploying ML models, or building LLM systems with prompting, tool use, agents, or retrieval.
- Experience with evaluation frameworks, simulations, production monitoring, or ML platform tooling.
Source et dates
Site carrière / système de candidatures · ashby
- Date publiée par l’employeur
- 2026-11-10
- Première détection par notre source
- 2026-11-10
- Mise à jour du dossier source
- 2026-11-10
Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.
Clera
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.
Your AI career agent. Warm intros to startups backed by a16z, Index, YC & more.
Description complète de l’entreprise
Your AI career agent. Warm intros to startups backed by a16z, Index, YC & more.
- Abonnés LinkedIn
- 7 288
- Personnes associées sur LinkedIn
- 14
- Bureaux déclarés
- San Francisco, US
- Berlin, DE
- New York, New York 10115, US
- Catégories d’activité
- Information Technology
- Recruiting
- Artificial Intelligence (AI)
- Autres noms enregistrés
- Clera
- Clera AI
- Clera-AI
- Spécialités
- headhunting
- jobs
- AI
- startups
- recruiting
- career
- and coaching
- Le profil indique une agence de recrutement
- Oui
- Investissement total déclaré
- 0
La devise et la date d’observation ne sont pas fournies; ce n’est ni une valorisation actuelle ni une ronde de financement.
Your AI career agent. Warm intros to startups backed by a16z, Index, YC & more.
| Champ | Valeur |
|---|---|
| Secteur | Technology, Information and Internet |
| Taille | 2-10 employees |
| Siège social | San Francisco |
| Type d’organisation | Privately Held |
| Fondée en | 2025 |
| Spécialités | headhuntingjobsAIstartupsrecruitingcareerand coaching |
| Offres sur Jobsy | 2 |
| Voir la page |
About the Role
Build and operate conversational AI systems that handle customer interactions over phone and SMS. This role spans product and ML platform work, from developing LLM-powered features to creating the tooling and evaluation systems that help teams deliver reliable production experiences.
What You'll Do
Build conversational AI systems that understand customer needs, take action, and escalate when appropriate.
Develop agent memory, knowledge graph, and customization tools to help systems adapt to different workflows.
Train, evaluate, and deploy models for prediction, classification, ranking, and capacity forecasting.
Create offline and online evaluations, simulations, and CI checks to detect regressions and measure production quality.
Build shared ML and LLM infrastructure for model serving, evaluation, observability, and product development.
Monitor and maintain production models and agents, and improve them based on measured results.
Contribute to technical reviews, documentation, and mentorship across engineering teams.
What We're Looking For
At least 6 years of software or machine learning engineering experience, including a track record of shipping and operating ML or LLM systems in production.
Strong Python skills and software engineering fundamentals, including writing reliable, maintainable, and testable code.
Experience building conversational AI for phone or SMS, or related real-time and streaming systems such as voice, SIP, or WebRTC.
Hands-on experience training and deploying ML models, or building LLM systems with prompting, tool use, agents, or retrieval.
Experience with evaluation frameworks, simulations, production monitoring, or ML platform tooling.
Familiarity with tools such as Ray Serve, Dagster, LiveKit, Vertex AI, GCP, Kubernetes, Pulumi, and AI provider APIs.
Comfort taking ownership from problem definition through production, working with ambiguity, and supporting teammates through reviews and mentorship.
Compensation & Benefits
Base salary range: CAD 200,000 to CAD 250,000 annually.
Location
On-site in Montreal, Quebec, Canada.
Journal
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