Auf einen Blick
- Aufgaben: Drive R&D in chemistry and materials using ML and AI, shaping our platform.
- Unternehmen: Quantistry Lab accelerates chemical simulations, making R&D faster and more efficient.
- Vorteile: Enjoy flexible hours, remote work, 30 vacation days, and a personal development budget.
- Weitere Informationen: We're an early-stage startup; your role can evolve as you grow with us!
- Warum dieser Job: Join a world-class team and make a real impact in the future of materials science.
- Qualifikationen: Bachelor's or Master's in a relevant field with 3+ years in ML/AI platforms and cloud experience.
Das prognostizierte Gehalt liegt zwischen 43200 - 84000 € pro Jahr.
Your Mission
As part of a world-class interdisciplinary team, you will drive materials discovery and development into a new era. Your work will accelerate the adoption of AI in chemistry and materials science, integrating and developing advanced solutions in our Quantum- and AI-powered materials intelligence platform, Quantistry Lab. You’ll play a pivotal role in shaping our technology, with significant freedom to define the model delivery pipeline, guide model development, and ensure seamless integration into our platform.
Your key responsibilities will include:
- Shape and enhance our ML/AI infrastructure, with strong support from our platform development team to implement best practices and efficient workflows
- Co-develop both existing and new ML/AI models, actively contributing to the end-to-end lifecycle from design through deployment
- Oversee data management operations in close collaboration with our platform team to ensure data quality and accessibility
- Regularly deploy code to production through our CI/CD pipeline, ensuring reliability and robustness in a live environment
Your Talents
- Bachelor’s or Master’s degree in a relevant field (e.g., Computer Science, Data Science, or similar)
- Demonstrated experience in building and/ormaintainingML/AI platforms
- Proven track record of deploying ML models in production environments, including dataset preparation and automation
- Minimum of 3 years’ experience working with cloud providers (AWS)
- At least 4 years of experience with Python or similar programming languages, with extensive experience in production environments
- Solid understanding of container orchestration tools like Kubernetes
- Hands-on experience in frameworks such as Kubeflow, MLflow, and/or Apache Spark
- Strong communication skills with a collaborative approach to working in an interdisciplinary team
- Experience or keen interest in data platform engineering is a plus
You might not tick all the boxes and that’s ok, apply anyways! Even though we have clearly defined roles, we are an early-stage startup and there are so many things to do that every team member can define their own role to a certain extent.
Your Package
- Flexible working hours and home office days.
- 30 days of vacation per year.
- Personal development budget of 1,000 EUR per year.
- Top-notch coffee at our favorite coffee shop next door for only 1 EUR.
- Free fruit and a large selection of drinks (including soda, juices, Mate).
- Work equipment of your choice.
- A competitive salary, reflective of your experience.
About us
Chemical simulations – this might sound abstract and academic but it’s much closer to everyday life than you think. Whether it\\\'s a smartphone, toothpaste, or the oil on a bicycle chain: all these products contain an incredible amount of chemical know-how. And in all these cases, the development process started in a lab at some point. During hundreds of development cycles, researchers have worked their way toward the optimal properties of a material or a chemical agent. Until the ideal conductivity of a semiconductor is achieved, or the desired viscosity of a cosmetic product is given. This takes a lot of time and, of course, a lot of money. We have the opinion that this can be done more easily nowadays! The Quantistry Lab - our cloud-native simulation platform - replaces countless development cycles in the lab. It reduces the costs of researching companies, accelerates their R&D, and improves their environmental footprint at the same time. Our customers think that’s pretty cool, and so do we. What about you? If you\\\'re ready to dive into the world of chemical simulations and make a significant impact, we\\\'d love to hear from you. Quantistry - The New Way to R&D
Additional Information
Quantistry is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, or genetic information.
Contact Information
Your contact person is Katja. If you have any questions, please send an email to career@quantistry.com. Please apply for this position only through our careers page at https://quantistry.com/career including your CV.
(Senior) Machine Learning Engineer (m/f/d) Arbeitgeber: Quantum On Demand
At Quantistry, we pride ourselves on being an exceptional employer that values innovation and collaboration. Our flexible working hours and commitment to work-life balance, combined with a personal development budget of 1,000 EUR per year, empower our employees to grow both personally and professionally. Join us in a vibrant work culture where your contributions directly impact the future of chemical and materials R&D, all while enjoying top-notch coffee and a supportive team environment.
StudySmarter Expertenrat🤫
Wir sind der Meinung, dass Sie so (Senior) Machine Learning Engineer (m/f/d) erhalten könnten
✨Tip Number 1
Familiarize yourself with the specific ML/AI frameworks mentioned in the job description, such as Kubeflow and MLflow. Having hands-on experience or even personal projects using these tools can set you apart during discussions.
✨Tip Number 2
Showcase your experience with cloud providers, especially AWS. If you have any relevant certifications or projects that demonstrate your ability to deploy ML models in production environments, be ready to discuss them.
✨Tip Number 3
Prepare to talk about your collaborative experiences in interdisciplinary teams. Highlight specific instances where your communication skills helped bridge gaps between different areas of expertise.
✨Tip Number 4
Research Quantistry Lab and its impact on R&D in chemistry and materials science. Being able to articulate how your skills can contribute to their mission will demonstrate your genuine interest in the role.
Wir glauben, dass du diese Fähigkeiten brauchst, um (Senior) Machine Learning Engineer (m/f/d) mit Bravour zu bestehen
Einige Tipps für deine Bewerbung 🫡
Tailor Your CV:Make sure your CV highlights relevant experience in machine learning and AI, especially any projects that demonstrate your ability to deploy models in production environments. Include specific technologies you've worked with, such as AWS, Python, and Kubernetes.
Craft a Compelling Cover Letter:In your cover letter, express your passion for integrating ML/AI into chemistry and materials science. Mention how your background aligns with the mission of Quantistry Lab and provide examples of how you've contributed to similar projects in the past.
Showcase Relevant Projects:When applying, include links or descriptions of projects that showcase your skills in building and maintaining ML/AI platforms. Highlight any experience with frameworks like Kubeflow or MLflow, and explain your role in those projects.
Follow Application Instructions:Ensure you apply through the specified careers page and include all required documents. Double-check that your application is complete and adheres to the guidelines provided in the job description.
Wie man sich auf ein Vorstellungsgespräch bei Quantum On Demand vorbereitet
✨Showcase Your ML/AI Experience
Be prepared to discuss your previous work with ML/AI platforms in detail. Highlight specific projects where you built or maintained models, focusing on the end-to-end lifecycle from design to deployment.
✨Demonstrate Cloud Proficiency
Since experience with cloud providers like AWS is crucial, be ready to share examples of how you've utilized cloud services in your past roles. Discuss any challenges you faced and how you overcame them.
✨Familiarize Yourself with Container Tools
Make sure you understand container orchestration tools like Kubernetes. Be prepared to explain how you've used these tools in your projects, especially in relation to deploying ML models.
✨Emphasize Collaboration Skills
Given the interdisciplinary nature of the team, highlight your communication and collaboration skills. Share examples of how you've successfully worked with diverse teams to achieve common goals.
