At ProteinQure, we are building a computational platform for design of protein therapeutics. Our mission is to help to create a world where drugs are engineered, not discovered. We work on treatments for cancer, diabetes, asthma, and cardiovascular diseases, among others, and partner with industry leaders in drug discovery to generate novel therapeutics outside of the conventional chemical space.
Our technology combines computational biophysical models with statistical and machine learning approaches to enable us to search across vast spaces of protein therapeutics. We build and deploy these computational modules using a scalable cloud computing infrastructure and complement their predictions with results from wet lab experiments. We utilize advanced computing architectures based on high-performance GPUs, TPUs and investigate novel methodologies in biophysical modelling and quantum computing.
ProteinQure is a seed-stage company and has raised its seed round of USD $4M led by top Silicon Valley and Canadian investors.
We're looking for a Machine Learning Lead to join our team in Toronto (Canada). You should think about joining us if you enjoy the balance of creating state-of-the-art machine learning algorithms but being evaluated by real-world impact. Our deliverables are molecules, not models. This is a player-coach role and will require a contribution to individual projects as well as managing a growing team.
ProteinQure is an interdisciplinary team and you will interact with world class experts in a variety of domains.
- Perform research and development of new methods for learning from protein sequence and structure datasets
- Unsupervised learning of protein/peptide sequence representation to assist in downstream machine learning engineering within the platform
- Development of supervised learning algorithms for protein structure prediction, protein-protein interaction prediction, and protein property prediction. This includes ML/Data Science models such as Gaussian processes, logistic regression etc in the context of creating new drugs.
- Work with data sets that are diverse in type and size (sparse data sets, 3D models, amino acid sequences, structural features)
- Work side-by-side with chemists, biologists, and software engineers to develop drug candidates
- Create culture and processes for machine learning team which balances research with applications
- Help build and manage a small ML team (2-3 others) in the context of a large computational R&D company
Nice to haves
- Peer-reviewed publications on applications of machine learning in biology, or new methods in natural language processing or geometric deep learning
- Experience with biology
- Experience working with developers with distributed version control (Git)
- Management experience
- Startup experience
- 2+ years work experience
- Have been part of machine learning team in a non-academic setting or deep experience with protein structure
- Willing to work at Toronto office 4 days a week
Benefits at ProteinQure include medical, dental and vision insurance and health spending account, which you can use on gym memberships or massages. We believe in enabling our employees to be their most productive selves - from extremely ergonomic chairs to standing desks and powerful, portable laptops. Employees are encouraged to buy (and get a refund for) equipment, books, or whatever tools that would make their work life easier.
The office is situated in downtown Toronto, with plenty of great restaurants nearby. Toronto is a great cultural hub (film festivals, theatres, museums and concerts) and supports active lifestyle (amateur sports leagues, waterfront beaches, surfing or even (ice) climbing). Canadian nature offers options for calming retreats and the country is very diverse, welcoming and open to newcomers.
The team composition is roughly 40% software engineers and data scientists, 40% computational biologists, medicinal chemists (including experimentalists performing experiments in wet lab) and 20% business and administration.
Celebration of diversity of all forms is embedded in our culture. Great work is the result of diverse thinking and experiences and we have a workplace where those differences can thrive. Over two thirds of the team was born outside of Canada.
Collaborative learning is at heart of what we do at ProteinQure - we have weekly lunch and learns (often with guest lecturers from outside of the company), attend (and organize!) meetups and hackathons and educate each other about best practices. We support our employees and sponsor attendance to conferences or professional events (up to $3000 a year).
Ownership of work is fundamental to way we operate. People will encourage you to problem solve and figure out how to best deliver results. You’re completely free to take vacation (and run errands) as long as you are responsible and performing. The last thing we want to do is micromanage our team. We try empower our employees, trust them to deliver and hold them accountable.
Our hiring process consists of three steps:
• Introductory call (30 min) - we want to get to know you, understand your motivations and needs. This is a chance to ask questions about the company!
• Technical interview (60 min) - Video (optional). We ask questions to understand your background a little bit better than your CV or GitHub profile can tell us.
• On-site interview (3 hours) - We try to be flexible on the timing of the on-site. If you are not from Toronto area, we’ll cover the travel and accommodation expenses.
We will give you our decision within 5 business days of the on-site interview. For the international candidates, we sponsor visas and help with relocation.