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- Aufgaben: Lead ML/AI projects from concept to deployment and optimize model performance.
- Arbeitgeber: Join CarOnSale, a Berlin-based start-up transforming the automotive B2B sector across Europe.
- Mitarbeitervorteile: Enjoy flexible tools, personalized coaching, and a vibrant team culture with regular events.
- Warum dieser Job: Make an immediate impact in a dynamic environment while growing your skills and network.
- Gewünschte Qualifikationen: Experience in machine learning, data science, and strong communication skills are essential.
- Andere Informationen: Be part of a diverse team that values inclusion and collaboration.
Das voraussichtliche Gehalt liegt zwischen 48000 - 84000 € pro Jahr.
CarOnSale, a dynamic Berlin-based start-up, is revolutionizing digital processes in the automotive B2B sector across Europe. We’re looking for a skilled Machine Learning Engineer to help drive innovation and make impactful changes in the automotive market.
Your Role
- Lead end-to-end ML/AI projects, from concept through deployment
- Coordinate with stakeholders, setting realistic expectations and ensuring clear communication for complex ML projects
- Convert data science prototypes into robust, production-ready solutions
- Design an operational framework for real-time model deployment, ensuring scalability and efficiency
- Apply advanced statistical techniques to extract actionable insights from data
- Establish processes and tools for monitoring and assessing model performance and data accuracy, maintaining best ML practices
- Continuously train and fine-tune models to optimize performance
- Collaborate with cross-functional teams to gain a deep understanding of business needs
- Partner with the product team to seamlessly integrate models and track outcomes
- Gather feedback from end-users to enhance models and products over time
- Mentor new team members in data science best practices and coding standards
- Work closely with other scientists, engineers, architects, and analysts to meet project milestones
- Take ownership of ML production system architecture, ensuring robust and scalable design
Why CarOnSale?
- Immediate Impact: Play a key role from day one in our mission to disrupt the European automotive market.
- Growth & Development: Access a comprehensive onboarding program, continuous feedback, and personalized coaching to support your growth.
- Tools of Your Choice: Choose between a MacBook or Windows laptop, along with all the software and hardware you need.
- Unique Culture: Become part of a passionate team with ambitious goals, enjoying regular team events and a strong COS spirit.
- Diversity & Inclusion: We value a truly diverse team where everyone feels comfortable and respected.
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Machine Learning Engineer (m/f/x) Arbeitgeber: CarOnSale
Kontaktperson:
CarOnSale HR Team
StudySmarter Bewerbungstipps 🤫
So bekommst du den Job: Machine Learning Engineer (m/f/x)
✨Tip Number 1
Familiarize yourself with the latest trends and technologies in machine learning and AI, especially those relevant to the automotive industry. This knowledge will not only help you during interviews but also demonstrate your genuine interest in the field.
✨Tip Number 2
Network with professionals in the automotive and tech sectors. Attend meetups, webinars, or conferences where you can connect with people who work at CarOnSale or similar companies. Personal connections can often lead to job opportunities.
✨Tip Number 3
Prepare to discuss specific projects you've worked on that showcase your ability to lead ML/AI initiatives. Be ready to explain your thought process, the challenges you faced, and how you overcame them, as this will highlight your problem-solving skills.
✨Tip Number 4
Showcase your collaborative skills by discussing experiences where you worked with cross-functional teams. Highlight how you communicated complex technical concepts to non-technical stakeholders, as this is crucial for the role at CarOnSale.
Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: Machine Learning Engineer (m/f/x)
Tipps für deine Bewerbung 🫡
Understand the Role: Make sure to thoroughly read the job description for the Machine Learning Engineer position at CarOnSale. Understand the key responsibilities and required skills, so you can tailor your application accordingly.
Highlight Relevant Experience: In your CV and cover letter, emphasize your experience with end-to-end ML/AI projects, particularly any work involving real-time model deployment and collaboration with cross-functional teams. Use specific examples to demonstrate your impact.
Showcase Technical Skills: Clearly outline your technical skills related to machine learning, data science, and programming languages. Mention any advanced statistical techniques you are familiar with and how you've applied them in past projects.
Personalize Your Application: Address your cover letter to the hiring team at CarOnSale and express your enthusiasm for their mission to disrupt the automotive market. Mention why you want to be part of their unique culture and how you can contribute to their goals.
Wie du dich auf ein Vorstellungsgespräch bei CarOnSale vorbereitest
✨Showcase Your Project Experience
Be prepared to discuss specific ML/AI projects you've led or contributed to. Highlight your role in the end-to-end process, from concept to deployment, and be ready to explain the challenges you faced and how you overcame them.
✨Understand the Business Context
Research CarOnSale and the automotive B2B sector. Understand their mission and how your skills can contribute to their goals. This will help you align your answers with their business needs during the interview.
✨Demonstrate Communication Skills
Since the role involves coordinating with stakeholders, practice explaining complex ML concepts in simple terms. Be ready to discuss how you ensure clear communication and set realistic expectations in your projects.
✨Prepare for Technical Questions
Brush up on advanced statistical techniques and model performance monitoring. Be ready to discuss how you would design an operational framework for real-time model deployment and optimize model performance over time.
