Machine Learning Engineer
MyneNetherlands14 hours ago
Full-timeEngineering, Information Technology
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Explore the forefront of innovative solutions for a sustainable future with us! We're seeking a passionate and hands-on Machine Learning Engineer to join our dynamic Technology team. If you're driven by innovation and eager to tackle challenges within and beyond your immediate expertise, this is the perfect opportunity.
About Myne
Myne Circular Metals is a leading company in the recycling industry, dedicated to solving the global problem of metal depletion and the environmental impacts of metal production. Leveraging creativity, perseverance, and cutting-edge technology, we are shaping the future of mining where today's goods become tomorrow's circular metals. With a team of 75 smart and driven employees in Harderwijk, the Netherlands, we generate an annual turnover of approximately 400 million euros. As we continue to develop new technologies and expand globally, our mission is to permanently change how metals are sourced at scale.
One of our key technologies is the Xorter, which converts metal waste into high-quality raw materials comparable to virgin metals, but at a lower cost. This breakthrough solution offers a true alternative to traditional recycling by avoiding downcycling and achieving circular metals. We collaborate closely with research institutions such as Delft University of Technology to enhance our capabilities. By leveraging advanced AI and robotics, we ensure high-quality metal recycling, delivering circular metals on demand, on recipe, and at the lowest cost.
Role Description
As a Machine Learning Engineer at Myne, you’ll be at the forefront of applied AI and deep learning techniques. Working within a collaborative and innovative environment, you’ll tackle complex challenges involving large-scale data, model training, and production deployment. We encourage a proactive, hands-on approach, where you'll contribute broadly and collaborate closely with a multidisciplinary team to build scalable, high-impact AI systems.
Key Responsibilities
Exited after reading this offer? We welcome your application, even if you don't meet all the listed criteria. Apply today and join us in shaping a sustainable future.
About Myne
Myne Circular Metals is a leading company in the recycling industry, dedicated to solving the global problem of metal depletion and the environmental impacts of metal production. Leveraging creativity, perseverance, and cutting-edge technology, we are shaping the future of mining where today's goods become tomorrow's circular metals. With a team of 75 smart and driven employees in Harderwijk, the Netherlands, we generate an annual turnover of approximately 400 million euros. As we continue to develop new technologies and expand globally, our mission is to permanently change how metals are sourced at scale.
One of our key technologies is the Xorter, which converts metal waste into high-quality raw materials comparable to virgin metals, but at a lower cost. This breakthrough solution offers a true alternative to traditional recycling by avoiding downcycling and achieving circular metals. We collaborate closely with research institutions such as Delft University of Technology to enhance our capabilities. By leveraging advanced AI and robotics, we ensure high-quality metal recycling, delivering circular metals on demand, on recipe, and at the lowest cost.
Role Description
As a Machine Learning Engineer at Myne, you’ll be at the forefront of applied AI and deep learning techniques. Working within a collaborative and innovative environment, you’ll tackle complex challenges involving large-scale data, model training, and production deployment. We encourage a proactive, hands-on approach, where you'll contribute broadly and collaborate closely with a multidisciplinary team to build scalable, high-impact AI systems.
Key Responsibilities
- End-to-End: Build and maintain scalable machine learning workflows, from data ingestion and preprocessing to model training, evaluation, and deployment.
- Data Management: Manage large datasets, ensure data quality, and design pipelines for training and evaluation.
- Model Development: Experiment with deep learning and classical ML models, optimize architectures, and benchmark performance.
- Collaboration & Innovation: Work closely with others engineers to integrate models into production and explore new technologies.
- Own & Troubleshoot: Lead ML projects end-to-end, troubleshoot issues, and ensure models perform robustly in production.
- Technical Expertise: Proven experience designing, training, and deploying models (PyTorch, TensorFlow, Keras, etc.)
- Data Expertise: Hands-on experience with data collection, filtering and labeling with large datasets.
- MLOps: Familiarity with Docker, CI/CD, model versioning, and monitoring; experience with MLflow, Label Studio, or similar is a plus.
- Problem-Solving Skills: Strong analytical and reasoning skills with the ability to visualize and present processes and outcomes. Natural curiosity and elevated observational skills are highly valued.
- Collaborative Spirit: Excellent communication and collaboration skills to effectively work within multidisciplinary teams and with external partners.
- Proactive & Adaptable: A positive attitude and the ability to thrive in a dynamic environment characterized by rapid change and a broad range of technical challenges.
- Groundbreaking Impact: Contribute to innovative recycling technologies to maximize sustainable impact in the industry.
- Pioneering Projects: Collaborate on cutting-edge initiatives with close ties to leading research institutions.
- Circular Economy Vision: Directly contribute to our circular economy journey and implement sustainable practices that matter.
- Inclusive Environment: Be part of a collaborative and inclusive culture that values diverse perspectives and teamwork.
- Professional Growth: Access to development and growth opportunities tailored to your career aspirations.
- Flexible Hours: Choose to work 32, 36, or 40 hours a week to suit your lifestyle and commitments.
- Performance Bonus: Your contributions to our success will be recognized with a yearly bonus.
- Comprehensive Benefits: Benefit from a full commuting allowance and a solid pension plan.
Exited after reading this offer? We welcome your application, even if you don't meet all the listed criteria. Apply today and join us in shaping a sustainable future.
Key Skills
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