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ML Engineer - Crypto

career-renew · 30+ days ago
Negotiable
Full-time
Remote
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Career Renew is recruiting for one of its clients an ML Engineer - Crypto - candidates need to be based in Canada.

We're searching for highly skilled ML Engineers to join our dynamic team. We're looking for someone who can bring their expertise in building AI products scoped to finance and crypto use cases, architecting an initial pipeline (with support from our infra team), and ultimately ship AI features that delight our customers. You'll spend your time on the following:

  • Development: Design, develop, and deploy machine learning models for various applications within the crypto finance domain, such as predictive analytics, fraud detection, transaction classification, and risk management.
  • Fine-tuning: Fine-tuning ML models for specific use cases, such as developing heuristics that detect fraudulent transactions, enhance reconciliation processes by analyzing historical transaction data, and provide greater explainability for the on-chain transactions our customers must later reconcile.
  • Deployment: Automating the deployment of ML models to production environments using tools and frameworks like Docker, Kubernetes, and CI/CD pipelines, ensuring high availability, low latency, and accuracy.
  • Monitoring: Implementing monitoring solutions to track model performance metrics, detect drift, and trigger re-training to maintain prediction accuracy and reliability.
  • Architecture: Improving the state of Integral’s architecture to unlock faster training and deployment cycles, working with the Platform Engineering team.
  • Collaboration: Collaborating with the full-stack engineering team to ensure seamless integration of ETL processes, data warehousing, and streaming to facilitate efficient model training and evaluation.

Requirements

Based in Canada

5+ years working on production web applications

Keen interest in working in crypto and building finance products

Built and deployed ML models into production

Ability to operate in an early-stage startup where much of the ML and data science infra is being built from scratch

Last updated on Aug 7, 2024

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