To date, the Silo AI team has already happily welcomed close to 40 incredibly talented colleagues during 2020, and we will be reaching the 100 people milestone soon. If you are interested in working at Silo AI, here are insights in the form of 7 most frequently asked questions that we have received while interviewing new Silopolis members!
1. Which AI technologies do you work with at Silo AI?
We have deep expertise especially in computer vision, machine learning and natural language processing with strong roots in academia. Our team of AI experts helps our clients in building AI solutions in industries such as automotive, maritime, heavy machinery, mobile, telecom, healthcare, infrastructure, energy, ports and logistics. Read more about our client project cases that we have made for Infranode in automated lead generation with NLP and Philips in improving radiotherapy planning with computer vision.
2. What does your current team look like?
We’re a growing team of almost 100 professionals and spread between three offices in Finland and international locations in Palo Alto and London. Our current team comes from 16 different countries and speaks 20+ different (natural) languages.
Most people define themselves as AI Scientists, AI Engineers, Software Developers, Solution Architects, Designers, you name it. What our people have in common is their interest in solving real-life problems within AI. And don’t worry, we do have a sales, marketing & comms, people and operations teams to keep everything running smoothly.
3. What is the difference between AI Scientist and AI Engineer roles at Silo AI?
Our AI Scientists and AI Engineers both build technical solutions to challenging ML/CV/NLP problems. AI Scientists have a strong academic background and PhD or PhD level skills and typically focus more on tasks that require research and prototyping. AI Engineers are the ones that can make prototype models work in the production environment, and this position requires more of a DevOps background. Our AI Scientists and AI Engineers work closely together in the project teams.
4. Are you an AI service company or a product company, or both?
This is one of the most common questions we get during the recruitment process. We are and remain a service company (aka consulting) that builds and delivers AI-driven products and solutions to our clients. With the intent to speed up delivery of projects, we are also building internal products in terms of development and deployment infrastructure. Our internal R&D team focuses on this product development.
5. What does your hiring process look like?
We like to meet candidates in person but also have capabilities to run our hiring process 100 % remote. Typically as a first step, we have an intro discussion, where we would go through your current situation, wishes for the future and what you are passionate about. You would also hear more about Silo AI, our culture, ways of working and our client projects. The most important part is to understand whether or not Silo AI is an interesting company for you and for us to see if we are able to provide matching opportunities.
For technical roles, the second step is a tech interview. This is your chance to get to know your future colleagues better and to see those people who are doing similar work at Silo AI. Depending on your area of expertise, you have a chance to meet for example Joni, Luiza, Emil or Niko during this step.
Third step sometimes is a take-home technical test. For example as an AI Scientist with machine learning expertise, you would do a machine learning related tech test.
As the final and the fourth step, we are normally ready to proceed towards the offer and to welcome you as a new Silopolis employee. If you would be working in our service side, we would be finding a suitable client project for you already during the process.
6. Do you have other options for employment or only full-time positions?
Yes, we do have! We are flexible when it comes to finding different employment options. You can either be a full-time Silo AI employee or work as an hourly-based employee to flexibly accommodate your other commitments (which usually imply academic faculty positions). On a case by case basis, we also involve freelancers in our projects. For academics like professors and postdocs we can also set up shared part-time positions between Silo AI and universities.
7. How do you support learning?
What is common for all Silopolis members, is the ongoing hunger to learn and develop. Keep Learning is actually one of our core values and to serve that we have created a concept called Learning lab. It consists of four different areas: research activities, group workshops, in-house talent coaching (by our senior experts like Jaakko), and internal communications. Learning lab further develops our best and most important quality – our expertise – and permits us to share knowledge and learn together. You also have a self-development budget to support your own individual learning goals – whether you want to get a certificate on a certain skill or take a course on something you deem useful for you.