Publié il y a 2 mois
AI Engineering Director
@ Scovai
Toronto, Ontario
En bref
Scovai, a talent acquisition and recruiting platform company, is hiring a full-time AI Engineering Director in a hybrid role in Toronto. The role owns AI/ML strategy end to end, including AI infrastructure, LLM-powered features and MLOps, and leads and grows engineering teams. The posting is a confidential search and states that the role is hybrid in Toronto.
Responsabilités :
- Own and drive AI/ML strategy end-to-end
- Lead design and delivery of scalable AI infrastructure and LLM features
- Build, mentor and scale engineering teams
- Partner with product, data and business stakeholders
- Direct development of intelligent agents across the platform
Résumé des exigences :
- Hands-on privacy-preserving ML experience
- Proven HR system integrations (ATS, HRIS, recruiting CRMs)
- Expertise in LLM performance and cost optimization
- Practical ML governance and anti-bias auditing in hiring
- Community contributions or external technical evangelism
Outils et compétences
Source et dates
Type de source non vérifié · apify-linkedin
- Date publiée par l’employeur
- 2026-09-03
- Première détection par notre source
- 2026-11-15
- Mise à jour du dossier source
- 2026-11-15
Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.
Détails du poste
| Niveau | Directeur ou directrice |
| Domaine | Développement logiciel |
| Gestion d’équipe | Oui |
| 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.
Scovai
| Champ | Valeur |
|---|---|
| Offres sur Jobsy | 2 |
CONFIDENTIAL Scovai, a trailblazer in the Talent Acquisition & Recruiting sector, is redefining how organizations build and manage their workforce through an intelligent, AI-powered talent platform that spans the entire employee lifecycle. As part of a confidential search, Scovai is seeking an exceptional AI Engineering Director to join their Toronto-based team in a hybrid capacity. This is a rare opportunity to shape the technical vision of a company at the forefront of transparent, auditable AI—where algorithmic precision meets human judgment to transform the future of work.
As AI Engineering Director, you will own and drive Scovai's AI/ML strategy end-to-end, leading the design and delivery of scalable AI infrastructure, LLM-powered features, and MLOps pipelines that underpin the platform's core capabilities. You will build, mentor, and scale high-performing engineering teams, partnering closely with product, data, and business stakeholders to translate ambitious roadmaps into production-grade AI systems. Your technical leadership will directly influence how intelligent agents are developed, deployed, and continuously improved across the platform.
This role is as exciting as it is impactful: you will operate at the intersection of cutting-edge generative AI research and real-world product delivery, with the autonomy to make foundational architectural decisions and the resources to execute them. If you thrive in high-growth environments, are passionate about responsible AI, and want to leave a lasting mark on an industry being fundamentally reimagined, Scovai offers the ideal stage.
Hands-on experience implementing privacy-preserving ML (differential privacy, federated learning, or secure multi-party computation) for sensitive talent/HR data Proven integrations with HR systems (ATS, HRIS, recruiting CRMs) and deep understanding of hiring workflows and data models Expertise in production LLM performance and cost optimization (model quantization, ONNX/Triton inference, vector DBs, and cloud cost management) Practical experience with ML governance, compliance, and anti-bias auditing in hiring contexts (GDPR/PIPEDA, EEOC considerations, model risk frameworks) Contributions to the ML/AI community (open-source projects, publications, or participation in standards bodies) or experience evangelizing technical strategy to external partners/customersNice to have
- Hands-on experience building generative AI products at scale
- Deep knowledge of transformer architectures and fine-tuning methodologies
- Background in data engineering and modern data stack design
- Proven track record scaling AI teams in startup or high-growth environments
- Open-source contributions to AI/ML frameworks or tooling
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