Machine Learning Engineer
Canada - Remote
Applications have closed
Teramind
Comprehensive user behavior analytics software for insider threat management, data loss prevention, workplace productivity, employee monitoring & moreTeramind is a hybrid, global workforce building the next-generation Insider Risk Management and User Behavior Analytics platform.
Join our team of innovators who are redefining insider risk management through cutting-edge technology. More than 10,000 organizations across the globe have used' Teramind to mitigate insider threats and protect their sensitive company data with the most robust, enterprise-grade software on the market.
As a global team, Teramind embraces an inclusive and flexible work environment and team culture. We win together, learn from each other and respect each other while delivering best-in-class security solutions.
About the role
This is a fantastic opportunity to shape the uses of advanced analytics and ML at Teramind. We're creating a space, "scaffolding", which will allow stats/ML models to be developed quickly by eliminating large-scale wrangling and defining a framework for deployment.
You will be designing, implementing, and maintaining the tools and systems that monitor the performance of our models in real-time, and provide insights and recommendations to improve their accuracy, reliability, and scalability. You'll bring a history of successfully implementing and deploying ML models in different environments using open-source frameworks that will shape this greenfield opportunity.
Your day-to-day
- Develop and use modern software engineering practices to deploy ML solutions at scale, including building CI/CD pipelines and automated testing
- Deploy and operationalize MLOps with a focus on model onboarding, operations, and monitoring of workflows; model evaluation and explainability, optimization of model hyperparameters, and version control; automation and scheduling of model training
- Support life cycle management of deployed ML model life cycle management (e.g. new releases, change management, monitoring, and troubleshooting)
- Support the MLOps Platform, including model registry, model deployment, and feature store.
- Knowledge of cloud-based and on-premise infrastructure and demonstrated ability to architect scalable services.
- Collaborate with internal teams for integrating ML models including defining SLAs and designing highly automated end-to-end testing.
- Stay current on ML infrastructure tech and advocate/educate the team about new developments by sharing resources, demos and PoCs .
Requirements
- 5+ years of software engineering or machine learning experience.
- Experience with building and maintaining infrastructure for model performance evaluation, including data collection, preprocessing, and analysis.
- Experience with open-source tooling and frameworks.
- Strong understanding of machine learning concepts and algorithms, and experience with developing and deploying machine learning models in production.
- Ability to modify and train open-source models.
- Experience with distributed model training and/or inference.
- Previous experience deploying systems for efficient batch or online ETL.
- An ability to maintain critical production software and build new production software from scratch.
- Prior experience working with product, engineering, and business to prioritize, scope, design, and deploy ML tooling and infrastructure at scale.
- Natural curiosity and desire to grow and help shape all aspects of our small and growing team.
- A degree (preferably graduate level) in Computer Science, Engineering, Statistics, Physics, Applied Math, or a related technical field.
Benefits
- Competitive salary with a focus on a global market.
- Career-growth opportunities.
- Flexible Time Off and Paid Time Off benefits.
- Ongoing training and development opportunities.
About our recruitment process
You can expect up to 4 interviews.
We don’t expect a perfect fit for every requirement we’ve outlined. If you can see yourself contributing to the team, we want to hear your story.
All roles require reference and background checks
Teramind is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration without regard to race, age, religion, color, marital status, national origin, gender, gender identity or expression, sexual orientation, disability, or veteran status.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: CI/CD Computer Science Engineering ETL Machine Learning Mathematics ML infrastructure ML models MLOps Model deployment Model training Open Source Physics Pipelines Security Statistics Testing
Perks/benefits: Career development Competitive pay Flex hours Flex vacation
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