Machine Learning Engineer

Toparo; Toronto; On-site; CAD 90,000 - 140,000; Full time

Job summary

A leading company in the Web3 and Blockchain space is seeking a talented Machine Learning Engineer in Toronto. You will design and deploy innovative ML solutions for the finance sector, focusing on predictive analytics and fraud detection. Join a dynamic team dedicated to solving complex challenges and leveraging cutting-edge technologies while enjoying competitive salary and perks.

Benefits

Flexible work arrangements

Competitive salary

Attractive equity options

Opportunities for growth

Exposure to cutting-edge technologies

Qualifications

• 5+ years of experience working on production web apps.
• Built ML models from scratch deployed in production.
• Hands-on with ML frameworks and orchestration tools.

Responsibilities

• Design, develop, and deploy ML models for crypto finance.
• Automate deployment of ML models using Docker and Kubernetes.
• Implement monitoring solutions to track model performance.

Skills

Machine Learning

Predictive Analytics

Fraud Detection

Risk Management

Problem Solving

Communication

Education

Bachelor's Degree in Computer Science

Tools

TensorFlow

PyTorch

Docker

Kubernetes

Apache Spark

Airflow

Job description

Are you seeking an exciting opportunity to work with groundbreaking, well-known Web3, Blockchain and Fortune 100 organizations?

Our client in Toronto is looking for a skilled Machine Learning Engineer to join their well-funded venture (USD 8.5M raised), focused on tackling unique treasury, accounting, and asset management challenges. They have processed over $100B in transactions in the last year!

About the Role :

As a Machine Learning Engineer, you will be at the forefront of innovation, collaborating with a dynamic team to shape the product vision and build AI products relating to finance and crypto.

We seek individuals with an entrepreneurial spirit, genuine enthusiasm for Web3 and Blockchain, and a passion for mastering web technologies and techniques. Your expertise will play a vital role in solving complex problems and driving the evolution of their products.

Responsibilities :

• Design, develop, and deploy machine learning models for various applications in crypto finance, such as predictive analytics, fraud detection, transaction classification, and risk management.
• Fine-tuning ML models for specific use cases, such as developing heuristics that detect fraudulent transactions, enhancing reconciliation processes by analyzing historical transaction data and providing greater explainability for the on-chain transactions our customers must later reconcile.
• 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.
• Implementing monitoring solutions to track model performance metrics, detect drift, and trigger re-training to maintain prediction accuracy and reliability.
• Working with the Platform Engineering team, improving the state of the company's architecture to unlock faster training and deployment cycles.
• 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.

Does this sound like you?

• 5+ years of experience working on production web apps
• Built ML models from scratch and deployed them into production environments
• Familiarity and interest in accounting, FinTech products, and / or crypto
• Hands-on experience with ML frameworks (TensorFlow, PyTorch)
• Hands-on experience with orchestration tools (Airflow, Docker, and Kubernetes)
• Experience with building and maintaining processing pipelines (Apache Spark, Airflow, or Kafka)
• A Bachelor's Degree in Computer Science or a related field or equivalent experience demonstrating your commitment to continuous learning and growth.
• Strong communication skills when interacting with tech and non-tech stakeholders

Perks and Benefits :

• The role is based in Toronto; local candidates open to coming onsite a few days a week are preferred.
• Flexibility in work arrangements, including remote opportunities.
• Competitive salary and attractive equity options to share in the venture's success.
• Opportunities for growth and taking on exciting responsibilities.
• Exposure to cutting-edge technologies
• Enjoy the fast-paced and dynamic environment of working at a startup, combined with the stability of a larger company
• Work alongside a world-class team from top tech companies

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