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Publié il y a 11 jours

ML Engineer – Generative AI & LLMs (Remote)

@ Ample Insight Inc.

Toutes ses offres Site Web

Toronto, Ontario

TélétravailContrat
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SIGNAUX

En bref

Ample Insight Inc. is hiring a Machine Learning Engineer on a remote contract basis to design, prototype and productize scalable ML solutions with LLMs and real-world data, working closely with clients and teammates. The role calls for strong LLM engineering and agentic systems experience, a Python ML stack background and a computer science or engineering degree. The posting states competitive compensation and an accountability-focused, non-micro-managed culture.

Responsabilités :

  • Design, prototype and productize scalable ML solutions
  • Build systems with LLMs and real-world data
  • Work closely with clients and teammates
  • Turn prototypes into production-ready services

Résumé des exigences :

  • Expertise in LLM engineering and provider best practices
  • Experience with agentic systems is a strong plus
  • Hands-on statistics and machine learning in Python
  • Proficiency with Git, Docker, SQL, Bash and FastAPI
  • Bachelor's degree or higher in computer science or related field

Outils et compétences

PythonPyTorchscikit-learnXGBoostPandasNumPyGitDockerSQLBash
Source et dates

Site carrière / système de candidatures · smartrecruiters

Date publiée par l’employeur
2026-10-30
Première détection par notre source
2026-10-30
Mise à jour du dossier source
2026-10-30

Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.

Détails du poste

DomaineRecherche et sciences
Milieu de travailDomicile
PositionSurtout assis
Exigences physiquesphysique faible · ordinateur élevé
LanguesEnglish
FormationBaccalauréat (exigé)
Domaines d’étudesComputer Science, Engineering

Résumé et détails rédigés par l’IA à partir de l’offre; l’offre de l’employeur fait foi.

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Ample Insight Inc.

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.

We build trusted AI and data solutions.

Description complète de l’entreprise

We are a team of world-class data scientists and software engineers who have helped top companies like Facebook, Google, Uber, Amazon, Microsoft and others solve some of their most difficult engineering problems. Have a quick question or need an experienced consulting advisor for a complex project that has 'been there and done that'​? We have you covered. Contact us today!

Abonnés LinkedIn
26 437
Personnes associées sur LinkedIn
14
Bureaux déclarés
  • 720 King St W, Suite 908, Toronto, Ontario M5V 3S5, CA
Catégories d’activité
  • Analytics
  • Artificial Intelligence (AI)
  • Machine Learning
Autres noms enregistrés
  • Ample Insight Inc.
  • Ample Insight
Spécialités
  • Data Science
  • Machine Learning
  • AI
  • Analytics
  • Computer Vision
  • Software Engineering
  • MVP
  • Data Engineering
  • Data Infrastructure
  • Data Governance
  • Generative AI
  • LLM
  • and ChatGPT
Le profil indique une agence de recrutement
Non
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.

Toutes ses offres Site Web

We are a team of world-class data scientists and software engineers who have helped top companies like Facebook, Google, Uber, Amazon, Microsoft and others solve some of their most difficult engineering problems. Have a quick question or need an experienced consulting advisor for a complex project that has 'been there and done that'​? We have you covered. Contact us today!

ChampValeur
SecteurData Infrastructure and Analytics
Taille11-50 employees
Siège socialToronto, Ontario
Type d’organisationPrivately Held
Fondée en2018
SpécialitésData ScienceMachine LearningAIAnalyticsComputer VisionSoftware EngineeringMVPData EngineeringData InfrastructureData Governance
Offres sur Jobsy8
LinkedInVoir la page
Description

Company Description

You will join a world-class team of engineers and data scientists from Facebook, Uber, Amazon and Google. We are a fast growing consulting firm based in Toronto with clients ranging from leading startups building impactful technologies to Fortune 500 companies looking to scale their engineering and data capabilities.

Job Description

We’re looking for Machine Learning Engineers who are passionate about building cutting-edge systems with LLMs and real-world data. In this role, you’ll work closely with clients and teammates to design, prototype, and productize scalable machine learning solutions.

You’ll be part of a collaborative, high-performing team that values clear thinking, pragmatic execution, and continuous learning. If you thrive in fast-paced environments, enjoy tackling open-ended problems, and care deeply about the quality and impact of your work, we’d love to connect.

Qualifications

  • Must have: Expertise in LLM engineering, including familiarity with popular LLM providers and their best practices. Experience building or working with agentic systems (e.g. tool use, memory, planning, multi-agent coordination) is a strong plus. Show us your LLM projects and detail your ownership and contributions.
  • Strong ability to rapidly prototype cutting-edge tools and research ideas, with a track record of turning prototypes into production-ready services.
  • Hands-on experience with statistics and machine learning. Comfortable working with the Python ML stack: Pandas, Numpy, scikit-learn, XGBoost, PyTorch, etc. Proficient with development tools such as Git, Docker, SQL, Bash, and FastAPI.
  • Strong analytical mindset and business acumen; able to think critically about data and its impact on product or business outcomes.
  • Bachelor's degree or higher (e.g., MS or PhD) in Computer Science or a related engineering field involving coding.
  • Bonus: Familiarity with AWS or Azure, GitHub Actions, Spark, Neo4j Cypher, and graph databases.

Additional Information

We have competitive compensation.

We believe in accountability and NOT micro-management.

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