Machine Learning Engineer
WS Audiology
Driven by the passion to improve quality of people’s lives, WS Audiology continues to grow as market leader in the hearing aid industry. With our commitment to increase penetration in an underserved hearing care market, we want to accelerate our business transformation in order to reach more people, more effectively.The roleThe role is for a Machine Learning Engineer to join a newly established team focused on applying state-of-the-art Artificial Intelligence and Machine Learning to transform internal workflows and tools at WSA. Your primary responsibility will be to develop impactful ML solutions and assist others in doing the same.Projects will be tightly focused and of small scope – typically lasting around 3 months, with a priority on those with the highest impact. The team will have a high degree of autonomy – in both choosing and executing projects. This role provides an excellent opportunity to experiment with a wide array of ML methods and domains, as well as the supporting tech stack for creating demos, prototypes, and MVPs.Keeping up with the trends in AI/ML will be part of the job and attending conferences is one way to achieve that. Another, is having regular reading groups where we discuss recent papers.The teamThis newly formed AI taskforce team will comprise of 3 new engineers and 1 senior/ lead engineer. This team is part of a larger AI center in the R&D branch, which includes 2 additional teams totaling around 15 people. Collaboration and knowledge sharing within the AI center are highly prioritized.We are a group of engineers with a mix of ML engineers, traditional software engineers, and researchers. We foster a low-overhead, informal culture focused on results and a “show, don’t tell” ethos.While some teams enjoy foosball for breaks and socializing, we prefer klask; a Danish-designed tabletop game. Some of the team members have even participated in local and national championships.Your profileYou have a Master’s Degree in computer science or related field. The ideal candidate has a mix of software and ML competencies – either approaching ML from a software/computer science background or from a mathematical background.You are fresh out of university or have only a few years of full-time employment behind you.We expect you to have experience with some of with the following core technologies and concepts:
– Python
– Modern ML and deep learning concepts and architectures, such as Transformers, Multimodal LLMs, Generative AI, Diffusion or Reinforcement Learning
– Deep learning tech stack, e.g., PyTorch or TensorFlow/KerasBesides those core concepts, we also value the following:
– Hands-on experience with LLMs-using, building, or training them-as they will likely be integral to many of our projects
– Experience with software development principles such as version control (Git), DevOps, code review, and programming principles (e.g., SOLID)
– Familiarity with cloud infrastructure like Azure, AWS, or Google Cloud
– Experience with other programming languages beyond Python, other tech stacks beyond AI (e.g., web or app development), and other technologies (e.g., hardware, VR)
For those eager to excel and contribute meaningfully to an international operations setting, we invite you to submit your application!Who we areAt WS Audiology, we provide innovative hearing aids and hearing health services.Together with our 12,000 colleagues in 130 countries, we invite you to help unlock human potential by bringing back hearing for millions of people around the world.With us, you will become part of a truly global company where we care for one another, welcome diversity and celebrate our successes.Sounds wonderful? We can’t wait to hear from you.WS Audiology is an equal-opportunity employer and committed to creating an inclusive employee experience for all. Regardless of race, color, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, medical condition, ancestry, disability, military or veteran status we firmly believe that our work is at its best when everyone feels free to be their most authentic self.
Lynge, Hovedstaden
Fri, 25 Oct 2024 23:46:40 GMT
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