Senior Software Engineer – Model Platform

Emploi pas sur LinkedIn

🕒 il y a 18 jours

🇨🇦 Canada – Télétravail

⏰ Temps Plein

🟠 Senior

🧑‍💻 Développeur Full-Stack

👻 Score fantôme 12%

Ce que ça veut dire : la probabilité que cette offre reste ouverte sans recrutement actif.Comment le lire : 60 % ou plus, on pense que c'est une offre fantôme. Un score plus bas est moins inquiétant.Comment on la calcule : ancienneté, republications, postes ouverts vs taille de l'équipe, rapidité de clôture, et si le salaire est indiqué.À noter : une estimation à partir de données publiques, pas un jugement sur l'entreprise. De vraies offres peuvent avoir un score élevé, alors prenez-le comme un indice, pas comme un fait.

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Abnormal Security

Site WebLinkedInTous les Emplois

501 - 1000 employés

🔒 Cybersecurity

Cybersecurity

Abnormal offre une protection totale contre la plus large gamme d'attaques, y compris le phishing, les logiciels malveillants, le ransomware, l'ingénierie sociale, l'usurpation d'identité d'exécutifs, le compromis de la chaîne d'approvisionnement, le compromis de comptes internes, le spam et le graymail.

Description

• Architect, design, build, deploy, and maintain Model Serving infrastructure supporting a world-class Detection Engine • Own projects scaling model serving and data processing services to handle 10x current traffic • Build the platform for fighting rapidly generated AI attacks • Own real-time and near real-time streaming pipelines and online feature serving services • Build Abnormal’s ML Training platform to improve MLE velocity and product precision and recall • Collaborate with MLE and Data Science teams by distilling feedback, correlating it to strategy, and executing • Coach and mentor junior engineers through 1-on-1s, pair programming, code reviews, and design reviews

🎯 Exigences

• 5+ years of experience as a Software Engineer or in a similar role, with hands-on experience building ML-engineering focused solutions • Experience maintaining large-scale distributed systems on cloud platforms such as AWS, GCP, or Azure • Strong grasp of cloud-based engineering best practices • Experience maintaining real-time and near real-time data pipelines or streaming services at high scale • Ability to collaborate effectively with cross-functional teams, including data scientists, machine learning engineers, product managers, and other stakeholders • Ability to translate requirements into actionable technical tasks, communicate progress clearly, and adapt to feedback • Excellent problem-solving skills and ability to work independently in a fast-paced environment • Familiarity with machine learning workflows and requirements supporting MLE teams, including feature development and serving at 50K+ QPS, offline/online equivalency, and large batch jobs for data gathering and training of tree and deep learning models • Experience with streaming data architectures and real-time processing • Knowledge of security and compliance frameworks related to data engineering and data privacy

🏖️ Avantages

• Pre-employment checks for successful candidates, in line with prevailing legislation and Abnormal AI's security and privacy standards • Equal opportunity employment