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.
What you’ll do:
- Design, research, test and recommend modern AI training, test and deployment strategies with application to microscope and ultrasound medical images
- Benchmark, analyze and improve performance of existing algorithms, and pre-processing and data augmentation strategies.
- Collaborate closely with other engineers to solve interesting and challenging data problems
- Turning prototypes of the computer vision algorithms into high quality product ready code
- Help establish an effective ML pipeline
- Advocate for code and process improvements across your team, and help to define best practices based on personal industry experience and research
- Participate in sprint planning, estimation and reviews. Take ownership of deliverables, and work with teammates to ensure high-quality deliverables
Who we’re looking for:
- Expert in Machine learning with experience in deep neural networks for computer vision problems, such as image classification and object detection preferably with medical imaging
- Strong understanding of Convolutional Neural Networks (CNN), Autoencoders and GANs
- Experience in image processing with emphasis on medical images
- A Master’s Degree or Ph.D. in Computer Science specializing in image processing, computational photography, computer vision or at least 5 years of experience in the industry or data science competitions
- Extensive experience in PyTorch deep learning framework and Python
- Familiarity with scientific computing libraries such as numpy, pandas, scikit and image processing libraries such as OpenCV and scikit-image.
- Familiarity with Git and Version Control Systems
- Experience running accuracy experiments and systematically improving performance
- You have 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
- Strong organizational and analytical skills
- Excellent written and verbal communication skills
- Attention to detail, data accuracy and quality of output
Bonus points for:
- Prior experience in applying image enhancement and segmentation on medical images and using image processing libraries
- Experience in “productizing” ML models
- Background in Life Science
- Experience with data processing frameworks
- Experience in privacy preserving or federated machine learning
- Research publications in ML/AI-related fields
|Job Category||Machine Learning|
|ML Experience||Over 5 years|
|Please attach your resume||PDF or DOC up to 5Mbps|