32 - 40 hours · Amsterdam
Hello, we are Quin's product tech team. A tech community of Kotlin/Spring Boot enthusiasts, React natives, Cloud huggers, and QA pros.
A community with a clear purpose: to develop scalable code that propels healthcare into the 22nd century.
Not for ‘the lucky few,’ but for everyone, everywhere. If that’s a purpose you can get behind, now is the time to team up because we are building next-gen, AI-driven doctor and patient-facing apps that effortlessly guide patients to the right medical assistance. We’re also reverse-engineering our Android and iOS apps as a web service.
Together with medical professionals (aches and pains? At Quin, there’s always a doctor in the room!) and data scientists. If a fluid environment where the (patient) stakes are high, autonomy is a given, and learning from hugely talented peers appeals to you, welcome to our development lab!
As our Machine Learning Engineer:You are on the hunt for an opportunity at the cutting edge of innovation in the field of Machine Learning and explainable AI, all while having an enormous positive impact on society.
You won't just contribute to building our AI engine; you'll also be an integral part of the smooth deployment, scalability, and maintenance of our machine learning solutions. By collaborating closely with medical experts and our dev/ops engineers, you'll bring substantial domain knowledge into vectorial representations and bridge the gap between model development and production.
You will:
- Craft, implement, and fine-tune machine learning algorithms, focusing on Retrieval-Augmented Generation and LLM.
- Partner closely with medical specialists to translate their expertise into our AI engine.
- Ensure seamless deployment, monitoring, and scalability of our ML models in production environments.
- Champion robust ML-Ops practices, including continuous integration, continuous delivery, and automated testing for ML systems.
- Collaborate with our tech team to construct a resilient, scalable infrastructure for our ML solutions.
- Monitor model performance, ensuring real-time diagnostics and speedy troubleshooting.
- Stay in the loop with the latest trends in AI, ML, and ML-Ops to continually push our boundaries.
How do you make us better?
If you are a Machine Learning Enthusiast and you:
- Hold a Master's/PhD in Computer Science, Machine Learning, or a related field.
- Demonstrate hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, and more.
- Possess a solid grasp of ML-Ops, including tools like Kubernetes, Docker, Jenkins, or similar.
- Proficient in Python and have experience with cloud platforms like AWS, Google Cloud, or Azure.
- Exhibit the ability to design and implement robust, scalable ML infrastructure solutions.
- Show exceptional problem-solving skills and an unwavering passion for continuous learning.
...then this job is right for you!
What's in it for you? We hope the opportunity to help future-proof healthcare with us gets your heart racing. That's what fuels our talented, international teammates, who are always eager to bounce ideas off each other, making learning from peers a daily experience.
We'll supercharge your learning curve as you work on the forefront of machine learning innovation and breakthroughs. Plus, our career development program will help you map your ideal Quin journey and empower you to reach your personal goals more quickly. As for the details, we'll reward your hard work with a competitive gross salary, depending on your seniority.
We support flexibility and work-life balance, offering a hybrid work environment. Our aim is 2-3 days per week at the office. Given our fantastic location (the former Netflix building), you might just find yourself gravitating towards HQ. Maybe for a friendly challenge in our gaming room, a delicious meal in our cafeteria, some fun bootcamps, or engaging in our regular learning sessions and lunch lectures. And yes, we provide relocation assistance from start to finish.
Ready to future-proof healthcare with us?Hit that healthy-looking button to set up a digital appointment. Or contact Andrew at a.kozma@quin.md for more info and an inspirational pitch.
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