Are you convinced AI can have a positive impact on our lives? Do you prefer applying ML technology to solve real-world problems today over pushing the boundaries of the state-of-the-art through academic research? Or put shortly: do you actively want to contribute to that positive impact, by raising the adoption of ML technology through actual use cases? Then the role of a Machine Learning Engineer will definitely trigger your interest!
In The Pocket's mission is to create digital products that make people happy and businesses grow. We believe both aspects are crucial for successful digital products, and they will often drive one another. Machine Learning technologies allow us to improve both: by improving the experience of existing products, by enabling new business models based on newly uncovered insights and by enabling a whole range of new digital products with new values streams.
- You'll closely collaborate with our product managers, architects, data engineers and software engineers to define, implement and improve use cases that are enabled through machine learning. It is your job to design, engineer, test, improve and deploy the actual model that is used, but you don't this in a vacuum. Rather, you're part of a multidisciplinary team where every member is equally responsible for the product's success.
- You keep up with the latest advances in the field of Artificial Intelligence, with a particular focus on what might be applicable in our context. In particular, your enthusiasm for "what is possible" motivates you and we expect you to transfer that enthusiasm to your team mates and even our clients.
- You actively participate in knowledge sharing both towards peers (lessons learned, new advances, process improvements,..) as well as other people in our organisation (e.g. sales, marketing, product, strategy...). And it doesn't have to stop there: we happily support any initiatives to share our findings with the world, through blogs, talks, podcasts or guest lectures.
- You clearly communicate and set expectations. What realistic results can be expected? What are the greatest risks/unknowns? Always be open and honest, and don't be afraid to ask for help.
- You hold a bachelor degree in AI Engineer or a master/PhD degree in Computer Science (or related), or you have a proven track record in a similar role.
- You have a profound knowledge of Python and the most important deep learning frameworks (Tensorflow, Keras, Pytorch,...).
- You have a broad awareness of the possibilities in the field of AI, but you are willing to build a more specialised expertise in the fields of computer vision and/or time series data.
- You have an affinity with product design and engineering top-notch digital products.
- You highly value the principles of clean code, continuous improvement and rapid prototyping. Experience with continuous delivery and/or devops practices is a plus.
- Any experience with the Google Cloud Platform, AWS or Azure is a plus.
On a personal level we are looking for a colleague who shares our values.
- Ownership: Working at In The Pocket means accepting a high level of autonomy. You take ownership and show the ability to decide and act for the good of the company.
- Integrity: Stick to your values, even when it doesn’t pay off in the short term. In The Pocket relies on trust and openness, which in turn relies on your integrity.
- Lead & Educate: Digital technologies are changing the world. We go all in, head-first. We take the lead in designing and building with emerging technologies. We share our passion and knowledge with as many people as possible.
- Agility: In The Pocket is permanently under construction. We never settle, it’s never done. Observing, adapting and improving is in our nature. That resonates with the people who work here. We are always looking for a better solution, always ready for the next step, pragmatic and committed to move forward.
- Team: As individuals we are bright and talented, as a team we’re unbeatable. We are open and positive, constructive and honest. We help and inspire our colleagues to do their best work