Research Manager, Machine Learning

Please apply if you want to: 
- Make a positive global impact on climate change and society- Work in an interdisciplinary environment where you are always learning - Grow as a leader and empower brilliant colleagues - Shape Machine Learning research tackling complex problems- Be part of a collaborative and sociable team- Join an established Machine Learning lab in a growth phase 
Invenia Labs’ Machine Learning Research Group design, prototype and train the algorithms which underpin our automated system for optimising electricity grids. As our team is growing, we are inviting you to join us in our mission to optimise the world’s complex systems for the benefit of as many people as possible, and lead this dynamic group. 

As the Machine Learning Group Lead, you will:

• Sculpt the role to your strengths and goals - we can be flexible depending on the individual. 
• Shape aspects of Invenia’s innovative research strategy. 
• Guide the Machine Learning Group’s professional development.
• Grow the group by attracting top Machine Learning talent.
• Maintain and improve the group’s open and collaborative culture.
• Nurture bottom-up idea generation and help to transform visions into plans. 
• Connect the dots and communicate between the group, the rest of the research team, and the rest of the company.
• Build strong relationships with both academia and industry, and keep up to date with the latest Machine Learning research.

About you:

• You have multiple years of experience in Machine Learning research.
• You have led a team (or teams) of Research Scientists or Research Engineers.
• You are an excellent communicator and presenter, who can explain complicated topics clearly and concisely.
• You can break down complex ambiguous problems and propose alternative solutions.
• You can build strong relationships and work with different teams in a fast-moving research environment.
• You want to improve your people leadership skills to a greater extent than technical skills
• You prefer building consensus and empowering others to solve problems over working alone or solving problems in isolation.

You might also have (optional):

• Experience with Bayesian methods, probabilistic modelling, optimisation, and/or statistical inference on complex data.
• Good software development skills, preferably experience with Python and/or Julia.
• Experience with numerical and scientific computing concepts and methods.
• Knowledge of electricity grids.

Please note that while this is a flexible hybrid role, it cannot be performed fully remotely. We only consider candidates who already live, or are willing to relocate to our office locations in either Winnipeg, Canada or Cambridge, UK.