Machine Learning Engineer

HRB; Toronto; On-site; CAD 80,000 - 120,000; Full time

Job summary

An innovative company is seeking a Senior Machine Learning Engineer to develop cutting-edge big-data machine learning toolkits. This role involves collaborating with a skilled team to transform prototypes into production-ready solutions while researching the latest techniques in the field. You'll have the opportunity to implement monitoring solutions and contribute to predictive modeling projects, ensuring data quality and model performance. Join a dynamic environment where creativity meets technology, and make a significant impact on the future of machine learning applications.

Qualifications

• 5+ years of experience in machine learning engineering.
• Excellent understanding of ML frameworks and libraries.
• Familiar with big data technologies like SQL and pyspark.

Responsibilities

• Collaborate with data scientists to develop production-ready ML solutions.
• Implement monitoring solutions for model performance and health.
• Contribute to predictive modeling projects using data mining techniques.

Skills

Machine Learning Engineering

Keras

TensorFlow

PyTorch

Python

SQL

pyspark

Data Structures

Algorithms

Education

BS in Computer Science

MS in Computer Science

PhD in Computer Science

Tools

scikit-learn

Big Data Technologies

Scala

Job description

Position Summary:
We are looking for a Senior Machine Learning Engineer, to work on developing large-scale big-data machine learning & solution automation toolkits and libraries. In this role, you will work with a talented engineering and data science team to develop a state-of-the-art ML framework that will enable hundreds of solutions and users, while also having the opportunity to research the latest machine learning techniques in industry and academia and then bring them into the Paytm Labs data scientist community.

What does this include?

• • Collaborate closely with data scientists to transform machine learning models from prototypes into production-ready solutions; work with data engineers to create robust data pipelines, ensuring data quality and appropriate feature engineering for model inputs
  • Develop and deploy monitoring solutions to track model performance, detect anomalies, and maintain model health; implement metrics to monitor and measure model and strategy impact
  • Implement strategies for retraining models in response to data drift and model performance degradation
  • Help to establish standards, approaches and implement required tooling and automation to support the full life cycle for model design and development which includes, but is not limited to identifying objectives, sampling, testing/validation, calibration, and monitoring performance
  • Contribute to the development of predictive modeling projects using data mining techniques for estimating current and future member engagement, operational performance, or other business outcomes; apply unsupervised learning methods to augment existing supervised models, or detect portfolio anomalies

Requirements:

• • 5+ years’ work experience as a Machine Learning Engineer or similar role.
  • Excellent understanding of machine learning frameworks (Keras/Tensorflow/PyTorch etc.) and libraries (scikit-learn, etc.).
  • Excellent understanding of computer science fundamentals, data structures, and algorithms.
  • Familiar with object-oriented design methodology and application development in Python.
  • Familiar with big data-related technologies to manage large volumes of complex data (SQL, pyspark).
  • Think outside of the box. Willing to have both hard work and have fun.
  • Ability to work in a team and highly collaborative
  • Working experience in fraud risk is a plus
  • Knowledge of Scala language is a plus
  • BS, MS, or PhD in Computer Science or related technical discipline (or equivalent).