Auf einen Blick
- Aufgaben: Design and implement MLOps workflows for model training, validation, deployment, and monitoring.
- Arbeitgeber: Join the leading software provider in healthcare, dedicated to improving lives through accessible medical information.
- Mitarbeitervorteile: Enjoy flexible mobile work, health-focused amenities, and opportunities for personal development.
- Warum dieser Job: Be part of a mission-driven team that values innovation and collaboration in the healthcare sector.
- Gewünschte Qualifikationen: Bring experience in ML engineering, cloud platforms, and strong communication skills in German and English.
- Andere Informationen: Diversity is celebrated here; all backgrounds are encouraged to apply!
Das voraussichtliche Gehalt liegt zwischen 43200 - 72000 € pro Jahr.
We are the leading provider of software in the healthcare sector. With our vision ‘No one should suffer or die just because some medical information is missing’, we want to create a culture that makes a sustainable contribution to the future of our healthcare system. Our work serves the goal of improving healthcare by ensuring that the necessary information is available anytime and anywhere.
Your contribution:
- You design and implement MLOps workflows for model training, validation, deployment, and monitoring, adhering to industry best practices.
- By closely collaborating with data scientists and software engineers, you ensure seamless integration and continuous improvement of machine learning models.
- You establish and promote company-wide best practices and support business units in adopting them.
- Additionally, you develop and maintain infrastructure for scalable and reliable machine learning operations and support the lifecycle management of deployed ML applications.
- Furthermore, you optimize CI/CD workflows for ML projects, ensure the security and performance of pipelines, and continuously improve MLOps processes while mentoring junior team members and potentially transitioning into a leadership role.
What you bring along:
- Several years of experience in ML engineering or supporting data science in a commercial environment, including deploying ML models
- Strong background in machine learning, data engineering or software development
- Experience with cloud computing platforms (AWS, GCP, Azure), machine learning frameworks (TensorFlow, PyTorch), CI/CD pipelines and automation tools (Jenkins, GitLab, MLflow, Kubeflow), Python for ML and automation tasks, experience with conainerizationd and orchestration tool (Docker, Kubernetes)
- Fluent in German and English
- Communication skills, team spirit and hands-on mindset
What you can expect from us:
- Mobile work: Work flexibly on the move two days a week and on site three days a week.
- Attractive locations: In addition to fully equipped workplaces, regular events such as summer parties and Christmas parties await you at our locations.
- Development: Our in-house academy and our portfolio of external co-operation partners will support you in your further development.
- Health: Health is a valuable asset for us. Our in-house canteen offers a selection of tasty and healthy dishes every day, and we welcome you to our fully equipped fitness centre for weekly courses (online & offline).
- More is always possible: The kindergarten on our CGM campus in Koblenz helps our employees to organise their working day even more flexibly. We also offer corporate benefits, the option of a job bike, a company pension scheme and much more.
Diversity is part of CGM! We look forward to receiving your application regardless of disability, gender, nationality, ethnic and social background, religion, age, sexual orientation and identity.
Convinced? Apply online now with your detailed application documents (including salary expectations and earliest possible starting date).
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Machine Learning Operations Engineer (m/f/d) Arbeitgeber: CompuGroup Medical
Kontaktperson:
CompuGroup Medical HR Team
StudySmarter Bewerbungstipps 🤫
So bekommst du den Job: Machine Learning Operations Engineer (m/f/d)
✨Tip Number 1
Familiarize yourself with the specific MLOps workflows and tools mentioned in the job description, such as TensorFlow, PyTorch, and CI/CD pipelines. This knowledge will help you speak confidently about your experience during the interview.
✨Tip Number 2
Highlight any previous experience you have in collaborating with data scientists and software engineers. Be prepared to discuss how you contributed to the integration and improvement of machine learning models in past projects.
✨Tip Number 3
Showcase your understanding of cloud computing platforms like AWS, GCP, or Azure. If you have hands-on experience, be ready to share specific examples of how you've utilized these platforms in your MLOps processes.
✨Tip Number 4
Emphasize your communication skills and team spirit, as these are crucial for the role. Prepare examples that demonstrate your ability to mentor junior team members and work collaboratively in a team setting.
Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: Machine Learning Operations Engineer (m/f/d)
Tipps für deine Bewerbung 🫡
Understand the Company Vision: Familiarize yourself with the company's mission to improve healthcare through accessible information. Reflect this understanding in your application to show alignment with their goals.
Highlight Relevant Experience: Emphasize your experience in ML engineering, particularly in deploying models and working with cloud platforms. Use specific examples that demonstrate your skills in MLOps workflows and CI/CD processes.
Showcase Technical Skills: Clearly list your technical proficiencies, especially in Python, machine learning frameworks, and containerization tools. Mention any relevant projects or achievements that illustrate your expertise.
Include Salary Expectations: As requested in the job description, be sure to include your salary expectations in your application. This shows that you have read the job posting carefully and are serious about the position.
Wie du dich auf ein Vorstellungsgespräch bei CompuGroup Medical vorbereitest
✨Understand MLOps Workflows
Make sure you have a solid grasp of MLOps workflows, including model training, validation, deployment, and monitoring. Be prepared to discuss how you've implemented these processes in previous roles and how you can contribute to the company's goals.
✨Showcase Your Technical Skills
Highlight your experience with cloud platforms like AWS, GCP, or Azure, as well as your proficiency in machine learning frameworks such as TensorFlow or PyTorch. Be ready to provide examples of how you've used CI/CD pipelines and automation tools in your projects.
✨Emphasize Collaboration
Since the role involves working closely with data scientists and software engineers, demonstrate your ability to collaborate effectively. Share examples of past teamwork experiences and how you contributed to successful project outcomes.
✨Prepare for Leadership Questions
As this position may lead to a mentorship or leadership role, be prepared to discuss your approach to mentoring junior team members. Think about how you can foster a culture of continuous improvement and best practices within the team.