Launched in February 2013, Swish is a fast-growing business with an innovative working culture and teams spanned across the world with teams in Toronto, San Francisco, Berlin, Auckland, Bruxelles, Medellin, and more.
We create products for successful business using cutting-edge technologies: Blockchain, Machine Learning, and Apps Dev. Working with Swish puts you in contact with prestigious brands, wherever your base is. We are a 100% remote-work company because we believe it is everyone’s choice to live and work the way they prefer.
Work is organized in sprints - 2 weeks periods to which, as a member of our talent community, you choose to commit. You always have the choice to accept or decline a sprint, or take-on multiple sprints simultaneously.
We let members choose what suits them best depending on their current situation: family, travel, studies, finance. We know life is not linear and we respect the humans behind the screens.
Our work ethic relies on six core values: Transparency, Directness, Meritocracy, Autonomy, Responsibility, Continuous Learning.
Ensuring a diverse and inclusive workplace where we learn from each other is core to our values. We welcome people of different backgrounds, experiences, abilities, and perspectives. We are an equal opportunity employer and a fun place to work.
Join the future of work today.
Use your extensive knowledge of machine learning to transform the way enterprises run their businesses. With a healthy pipeline of projects ranging from insurance modeling, call center automation, social listening, and text analytics, we are looking to bring on passionate experts to solve the challenges of automation at scale and help our clients capitalize on the power of machine learning and data science.
The Machine Learning Engineer role is responsible for building AI systems that can achieve unprecedented levels of performance. This requires designing, implementing, and improving distributed machine learning systems at large scale with quality code, and leveraging the science behind the algorithms employed.
A Typical Week
You'll be tasked with developing machine learning techniques and applying them at scale to our projects. We look for the following attributes in candidates:
In all cases, you should be motivated by a desire to solve the most important problems and obtain unprecedented results and eager to push your methods to their maximal performance.