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- Aufgaben: Lead a talented team in developing impactful ML models for healthcare.
- Arbeitgeber: Join a dynamic team dedicated to enhancing medical services through innovative technology.
- Mitarbeitervorteile: Enjoy a fully remote position with a global team of experts.
- Warum dieser Job: Make a real difference in healthcare while growing your leadership skills in a collaborative environment.
- Gewünschte Qualifikationen: 5 years in machine learning and 2 years in a leadership role required.
- Andere Informationen: Nice-to-have: experience in healthcare projects and familiarity with GCP.
Das voraussichtliche Gehalt liegt zwischen 48000 - 84000 € pro Jahr.
The company is a team of experts providing analytical services to healthcare clients and is looking for a talented long-term ML Team Lead. You will join an international team of first-class professionals who are passionate about creating products that improve the quality of medical services.
Responsibilities:
- Team Leadership and Development: Lead a team of 7-10 professionals including data engineers, data scientists, MLOps engineers, and QA specialists. Create a collaborative and productive environment and support team members‘ technical and professional growth.
- Technical Task Planning and Prioritization: Work with the Product Manager to understand business goals, set task priorities, and manage team resources effectively. Recommend task prioritization strategies to increase product impact and efficiency.
- Technical Oversight and Quality Assurance: Lead the team through all stages of model development from design to deployment, ensuring best practices in code quality, documentation, and reproducibility. Set clear, repeatable documentation standards to support scalability and knowledge sharing. Implement systems to monitor model performance and keep ML services stable.
- Architectural Solution Design and Review: Propose and evaluate technical solutions to meet project goals and present these solutions to IT architects and the CTO. Participate actively in technical discussions to ensure solutions fit organizational standards and long-term plans.
- Cross-Functional Collaboration: Work closely with other teams (e.g., SecOps, DevOps, UI) to ensure ML models integrate smoothly with the overall system and align with other technical projects. Interact with the business and explain the results of your analysis.
Requirements:
- 5 years in machine learning with hands-on model development experience.
- 2 years in a technical leadership role.
- Practical experience with Git, Airflow, and MLflow (or similar tools).
- Strong Python skills with experience using popular ML libraries and tools (e.g., PyTorch, Hugging Face, Transformers, etc.).
- Experience with cloud platforms (AWS, GCP, Azure), especially their ML and data engineering services.
- Advanced SQL skills and experience building/managing data pipelines with Airflow or similar tools.
- Understanding of MLOps practices including CI/CD for ML.
- Familiarity with Kubernetes for ML service deployment and management.
- English level B2 or higher.
Nice-to-have skills:
- Experience in healthcare or medical insurance projects.
- Experience with Google Cloud Platform (GCP).
- Knowledge of Document Recognition, NLP, OpenCV, LLM.
Benefits:
- Fully remote job.
- Opportunity to work with an international team of first-class professionals.
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IT-Consultant Netzwerk / IT-Security (w / m / d) - System Engineering / Admin, Consulting, IT-S[...] Arbeitgeber: interface systems
Kontaktperson:
interface systems HR Team
StudySmarter Bewerbungstipps 🤫
So bekommst du den Job: IT-Consultant Netzwerk / IT-Security (w / m / d) - System Engineering / Admin, Consulting, IT-S[...]
✨Tip Number 1
Make sure to highlight your leadership experience in machine learning. Since the role involves leading a team of professionals, showcasing your ability to foster collaboration and support team growth will set you apart.
✨Tip Number 2
Familiarize yourself with the specific tools mentioned in the job description, like Git, Airflow, and MLflow. Being able to discuss your hands-on experience with these tools during the interview will demonstrate your technical proficiency.
✨Tip Number 3
Prepare to discuss your experience with cloud platforms, especially AWS, GCP, or Azure. Highlight any projects where you've utilized their ML and data engineering services, as this is crucial for the role.
✨Tip Number 4
Since the position involves cross-functional collaboration, think of examples where you've successfully worked with other teams. Being able to articulate how you ensured smooth integration of ML models with other systems will be beneficial.
Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: IT-Consultant Netzwerk / IT-Security (w / m / d) - System Engineering / Admin, Consulting, IT-S[...]
Tipps für deine Bewerbung 🫡
Understand the Role: Make sure to thoroughly read the job description and understand the responsibilities and requirements. Tailor your application to highlight your relevant experience in machine learning, team leadership, and technical oversight.
Highlight Relevant Experience: In your CV and cover letter, emphasize your 5 years of experience in machine learning and any specific projects where you led a team or developed models. Mention your familiarity with tools like Git, Airflow, and MLflow, as well as your cloud platform experience.
Showcase Technical Skills: Clearly outline your technical skills, especially in Python and popular ML libraries. Provide examples of how you've used these skills in past projects, particularly in healthcare or similar fields if applicable.
Craft a Compelling Cover Letter: Write a personalized cover letter that explains why you're passionate about the role and how your background aligns with the company's goals. Discuss your approach to team leadership and collaboration, and how you can contribute to improving medical services through ML.
Wie du dich auf ein Vorstellungsgespräch bei interface systems vorbereitest
✨Showcase Your Leadership Skills
As a potential team lead, it's crucial to demonstrate your leadership experience. Share specific examples of how you've successfully led teams in the past, focusing on how you foster collaboration and support professional growth.
✨Highlight Technical Expertise
Be prepared to discuss your hands-on experience with machine learning tools and frameworks. Highlight your proficiency in Python, Git, Airflow, and any relevant cloud platforms, ensuring you can articulate how these skills will benefit the team.
✨Discuss Cross-Functional Collaboration
Emphasize your ability to work with various teams, such as SecOps and DevOps. Provide examples of how you've successfully integrated ML models into larger systems and how you communicate technical concepts to non-technical stakeholders.
✨Prepare for Technical Discussions
Expect to engage in technical discussions about architectural solutions. Be ready to propose and evaluate solutions that align with organizational standards, showcasing your understanding of MLOps practices and CI/CD for ML.
