Future Fertility Career Openings
Machine Learning Engineer
Toronto, ON, Canada .
full-time . August 31, 2022
Description
Who we are:
Future Fertility is a Canadian start-up located in Toronto. We develop and market AI-enhanced software solutions in the high-growth market of Assisted Reproductive Technology (ART). We have been chosen by MaRS, North America’s largest urban innovation hub, to be showcased as one of their portfolio companies. We are trusted by some of the best IVF clinics in North America and Europe and have successfully raised a Series A financing round. The investment was led by M Ventures (the corporate venture capital arm of Merck KGaA, Darmstadt, Germany, a global fertility leader), with participation from Whitecap Venture Partners.
Insights yielded by this patented software technology will be invaluable to patients, clinicians, and researchers. To learn more, please visit: https://futurefertility.com/ .
We continue to invest in developing further solutions to deliver on our goal for radically improved levels of insight for patients and clinicians by using artificial intelligence, and in so doing, substantially improve the experience and outcomes.
Who we are looking for:
An experienced Machine Learning Engineer to develop our next-generation image classification tool, using machine learning and computer vision techniques. You will be implementing algorithms by fast prototyping, converting them to production models and working with the development team to deploy the solution. This position requires excellent skills with Python and its machine learning and image processing libraries.
Working knowledge of Web development is a bonus.
What you’ll do:
- Take ownership of the machine learning project from start to finish, which includes building data pipelines, designing, deploying & maintaining production quality ML models in collaboration with data scientists.
- Data Acquisition, Cleaning, and Transformation in order to prepare training datasets.
- Build, train, and evaluate image classification and segmentation models using different architectures and tools.
- Benchmark, analyze and improve performance of existing algorithms, pre-processing and data augmentation strategies.
- Turning prototyped computer vision algorithms into high performance product ready code.
- Serve deep learning based computer vision models using the latest serving technologies.
- Providing support to the dev team on integrating ML systems with our software stack.
- Participate in sprint planning, estimation and reviews and take ownership of deliverables
- Document all machine learning processes and findings in an organized manner
Qualification:
- Bachelor or Master in Computer Science, Computer Engineering, Machine Learning, Statistics or Mathematics.
- 5+ years of experience in software development and data manipulation; Expertise writing code in Python
- 2+ years of experience in building and implementing production scale Machine Learning models in professional working environment
- Extensive experience in PyTorch deep learning framework
- Solid understanding of foundational statistics concepts and ML algorithms: linear/logistic regression, Random Forest, boosting, XGBM, k-NN, Naive Bayes, Decision Trees, SVM, etc.
- Good theoretical as well as practical knowledge of deep learning architectures such as LSTM, RNN and CNN and Transformer based models
- Algorithm and model development experience for large-scale applications.
- Experience running accuracy experiments and systematically improving performance.
- Familiarity with scientific computing libraries such as numpy, pandas, scikit and image processing libraries such as OpenCV and scikit-image.
- Solid understanding and practical experience of containerizing Deep Learning models for deployment purposes in a scalable manner.
- Experience with SQL and NoSQL databases and ETL tools.
- Familiarity with Git.
- Strong cross-team communication and collaboration skills. Comfortable being part of a small team of engineers working in an energetic fast paced start-up environment and effective as part of a distributed team.
- Excellent written and verbal communication skills.
- Attention to detail, data accuracy and quality of output.
Bonus points for:
- Experience in image processing
- Prior experience in applying image enhancement and segmentation on medical images and using image processing libraries
- Have prior experience of MLOps such as MLFlow
- Background in Life Science
- Experience in privacy preserving or federated machine learning
- Research publications in ML/AI-related fields