Machine Learning Engineer (Americas - Remote)
United States
Applications have closed
FreshBooks
The best cloud based small business accounting software. Send invoices, track time, manage receipts, expenses, and accept credit cards. Free 30-day trial.Machine Learning Engineer
FreshBooks has an ambitious vision. We launched in 2003 but we’re just getting started and there’s a lot left to do. We're a high-performing team working towards a common goal: building an elite online accounting application to help small businesses better handle their finances. Known for extraordinary product and customer service experiences and based in Toronto, Canada, FreshBooks serves paying customers in over 120 countries, with offices in the U.S., Netherlands and Croatia.
The Opportunity
We are looking for an experienced Machine Learning Engineer to build and support the delivery of machine learning-driven features for our platform. The perfect candidate has deep technical skills and is comfortable working in an evolving technology infrastructure. This is a unique opportunity to join a growing team of creative and passionate individuals committed to solving real world problems with modern ML practices.
The role will collaborate with data scientists and data engineers, to convert trained models to data products that power various user-facing features and internally focused tools. The ML engineer will be responsible for bringing the best software development practices to the data team and building out an MLOps practice.
What you’ll do:
- Work with data scientists to get Machine Learning models into production.
- Build end-to-end Machine Learning pipelines in support of data analysis and machine learning tasks.
- Transform ML prototypes into data products that can be used by different business units.
- Optimize current ML models built by data scientists for performance and scalability.
- Provide support to Data Engineers to ensure reliable data flows between different parts of the data ecosystem.
What you bring:
- Bachelor's degree in Computer Science or similar discipline, Master’s degree preferred
- 3-5 years of previous experience in a senior role in Software Engineering and/or applied Machine Learning shipping data products with implementation in low-latency real-time platforms and/or scalable offline batch processes.
- Excellent programming and algorithmic skills:
- Solid experience with Python / SQL
- Experience with data processing and Machine Learning libraries (e.g., TensorFlow, Keras, NumPy, SciPy, Pandas, Scikit-learn)
- job scheduling technologies (e.g., Airflow, Kubeflow, DBT)
- containerization for isolated development (Docker, Kubernetes).
- Knowledge of REST APIs.
- Familiarity with Google Cloud Platform tools (AWS and/or Azure are also good).
- Experience with MLOps and CI/CD for ML enabled applications.
Why Join Us
We're a motivated bunch, with our eyes laser-focused on shipping extraordinary experiences to businesses. You will be surrounded by hardworking team members who share a common vision for what an amazing software company could be, and have the opportunity to help build an elite one, right here in downtown Toronto.
Apply Now
Have we got your attention? Submit your application today and a member of our recruitment team will be in touch with you shortly!
FreshBooks is an equal opportunity employer that embraces the differences in all of our employees. We celebrate diversity and are committed to creating an inclusive environment for all FreshBookers. All applicants are evaluated based on their experience and qualifications in relation to this position.
FreshBooks provides employment accommodation during the recruitment process. Should you require any accommodation, please indicate this on your application and we will work with you to meet your accessibility needs. For any questions, suggestions or required documents regarding accessibility in a different format, please contact us at phone 416-780-2700 and/or accessibility@freshbooks.com.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Airflow APIs AWS Azure CI/CD Computer Science Data analysis Docker Engineering GCP Google Cloud Keras Kubernetes Machine Learning ML models MLOps NumPy Pandas Pipelines Python Scikit-learn SciPy SQL TensorFlow
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