Senior Machine Learning Engineer

Senior Machine Learning Engineer

Toronto, Ontario, Canada  - Permanent

Job Description

Our client are a leading provider of cutting-edge software solutions, specializing in fraud risk management. Their innovative SaaS platform helps businesses mitigate fraud risks, protect sensitive data, and maintain trust with their customers.

If working with billions of events, petabytes of data, and optimizing for the last millisecond is something that excites you then read on! We are looking for Senior Machine Learning Engineers who have seen their fair share of messy data sets and have been able to structure them for further fraud detection and prevention; anomaly detection and other AI products.

You will be working on writing frameworks for real-time and batch pipelines to ingest and transform events from 100’s of applications every day. These events will be consumed by both machines and people. Our ML and Software engineers consume these events to build new and optimize existing models to detect and fight new fraud patterns. You will also help optimize the feature pipelines for fast execution and work with software engineers to build event-driven microservices.

You will get to put cutting-edge tech in production and the freedom to experiment with new frameworks, try new ways to optimize, and resources to build the next big thing in fintech using data!

What does this include:

We are looking for a 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.
● 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

Must Have Skills:

● 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).


Starting: ASAP
Travel: 25%
Dress Code: Casual

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