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Machine Learning Engineer (f/m/d)

adjoe is a leading mobile ad platform developing cutting-edge advertising and monetization solutions that take its app partners’ business to the next level. Part of the applike group ecosystem, adjoe is home to an advanced tech stack, powerful financial backing from Bertelsmann, and a highly motivated workforce to be reckoned with.


Meet Your Team: WAVE Data Science


Did you know that in-app ads are sold in a real-time auction before they get rendered in thousands of mobile apps? Dozens of ad networks compete for every single view, choosing their best ad and deciding what price to bid in just a couple hundred milliseconds. We at adjoe have developed our own ad network that takes part in this competition, fighting against giants like Google, Meta and TikTok to present its own ads. To stand a chance in this fierce competition, the WAVE Data Science team builds creative algorithms using technologies ranging from simple linear regression to advanced deep learning models. Everything we do is based on solid research about user behavior as well as publisher and advertiser analysis to build competitive bidding algorithms that balance the advertisers’ goals, the publishers’ expectations and of course the user experience. To make our inventions come to life we use state-of-the art technology and work closely with the product and business teams to shape the future of adjoe’s core business and technologies.


What You Will Do
  • Dive into state-of-the-art algorithms and deep learning models to create recommendation systems, predict user behavior, and optimise user retention.
  • Conduct bidding algorithm experiments end-to-end: from idea generation and research to deployment to production, monitoring and decision making based on the results.
  • Dive deep into the technical implementation of our algorithms and optimise them for use in production.
  • Build systems to monitor technical and business KPIs in real-time.
  • Act as an advocate for data-related topics in the company and become the go to person in your area of expertise.


Who You Are
  • You have 2+ years of professional experience in the Data Science field building recommendation systems or similar (for example in adtech, retail, search, ranking).
  • You have shown a great level of understanding of deep neural networks (libraries such as TensorFlow and PyTorch) and have experience developing deep neural networks for recommendation systems.
  • You have already deployed machine learning models to production yourself and you know how to monitor them.
  • You have a strong knowledge of Python, R, Scala, Julia or similar typical programming languages for Data Science and have experience writing production-ready code in it
  • You have experience drilling into large amounts of data coming from various sources – including AWS Athena, Kafka, Spark, Flink, S3, MySQL.
  • You are able to dive deep into mathematical foundations and explain complex topics in a simple way.
  • You are a strong team player and enjoy helping others.
  • Generating new ideas and solutions to problems, even unconventional ones, is something that brings you joy and that’s easy for you.
  • Plus: Experiences in deep cross networks and multi-task deep learning.
  • Plus: You have hands-on experience working with common Data Science / Machine Learning tools in production, for example TensorFlow, TensorFlow Serving, Airflow, Flink, Kafka, Terraform or other tools from our Tech Stack.


Heard of Our Perks?
  • Work-Life Package: 2 remote days per week, 30 vacation days, 3 weeks per year of remote work, flexible working hours, dog-friendly kick-ass office in the center of the city.
  • Relocation Package: Visa & legal support, relocation bonus, reimbursement of German Classes costs and more.
  • Happy Belly Package: Monthly company lunch, tons of free snacks and drinks, free breakfast & fresh delicious pastries every Monday
  • Physical & Mental Health Package: In-house gym with personal trainer, various classes like Yoga with expert teachers.
  • Activity Package: Regular team and company events, hackathons.
  • Education Package: Opportunities to boost your professional development with courses and trainings directly connected to your career goals 
  • Wealth building: virtual stock options for all our regular employees.


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$70000 / YEARLY (est.)
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$60000K
$80000K

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What You Should Know About Machine Learning Engineer (f/m/d), AppLike Group

Are you ready to dive into the exciting world of data and algorithms? At adjoe, a leading mobile ad platform based in Hamburg, we’re on the hunt for a talented Machine Learning Engineer (f/m/d) to join our innovative WAVE Data Science team. Our team specializes in pushing the boundaries of how in-app advertising works, developing cutting-edge algorithms that compete in real-time against giants like Google and Meta. As a Machine Learning Engineer, you will explore a range of technologies to create sophisticated recommendation systems, optimize bidding algorithms, and elevate user retention strategies. You’ll have the chance to conduct experiments from inception to deployment while working alongside product and business teams to set new standards in adtech. We’re not just looking for someone with technical skills – we want a proactive team player who can turn complex problems into simple solutions and bring fresh ideas to the table. With over 2 years of experience in Data Science, proficiency in deep learning libraries like TensorFlow, and a knack for analyzing large datasets, you’ll thrive in our dynamic environment. Plus, we offer an array of perks to ensure a well-rounded and enjoyable work experience, from flexible working hours to a fully equipped office in downtown Hamburg. If you’re excited about leveraging your skills to shape the future of adtech at adjoe, we’d love to hear from you!

Frequently Asked Questions (FAQs) for Machine Learning Engineer (f/m/d) Role at AppLike Group
What does a Machine Learning Engineer (f/m/d) do at adjoe?

At adjoe, a Machine Learning Engineer (f/m/d) plays a critical role in developing advanced algorithms for our mobile ad platform. This position includes creating recommendation systems, optimizing bidding algorithms, and improving user retention strategies through experimentation and deployment of machine learning models.

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What qualifications are needed for the Machine Learning Engineer (f/m/d) position at adjoe?

Candidates applying for the Machine Learning Engineer (f/m/d) role at adjoe should have over 2 years of professional experience in Data Science, particularly in building recommendation systems. Familiarity with deep learning libraries like TensorFlow or PyTorch and a strong coding background in Python or similar languages are also essential.

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What technologies does adjoe's Machine Learning Engineer (f/m/d) work with?

In the Machine Learning Engineer (f/m/d) role at adjoe, you will work with various technologies and programming languages, including TensorFlow, AWS Athena, Kafka, and Flink, to analyze large data sets and deploy machine learning models into production effectively.

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What is the work culture like for a Machine Learning Engineer (f/m/d) at adjoe?

The work culture at adjoe for a Machine Learning Engineer (f/m/d) is collaborative and innovative, with a strong emphasis on teamwork and creativity. Employees enjoy a flexible work-life balance along with various perks that promote both physical and mental well-being.

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What kind of projects will a Machine Learning Engineer (f/m/d) engage in at adjoe?

A Machine Learning Engineer (f/m/d) at adjoe will engage in exciting projects that involve crafting and optimizing algorithms that enhance in-app advertising strategies through real-time bidding analysis and user behavior predictions.

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What benefits can a Machine Learning Engineer (f/m/d) expect at adjoe?

adjoe offers an attractive benefits package for a Machine Learning Engineer (f/m/d) that includes flexible working hours, a remote work option, relocation support, a generous vacation policy, opportunities for professional development, and wellness initiatives.

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How can I prepare for an interview for the Machine Learning Engineer (f/m/d) position at adjoe?

To prepare for an interview for the Machine Learning Engineer (f/m/d) position at adjoe, focus on understanding machine learning concepts, your experience with relevant technologies, and be prepared to discuss your past projects in detail, especially those involving recommendation systems and data analysis.

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Common Interview Questions for Machine Learning Engineer (f/m/d)
Can you describe your experience with TensorFlow or PyTorch?

In answering this question, elaborate on specific projects where you utilized TensorFlow or PyTorch, the type of models you built, and how you optimized their performance. Highlight any challenges faced during the projects and how you overcame them.

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What techniques do you use to evaluate the performance of your machine learning models?

Discuss various metrics like accuracy, precision, recall, and F1 score, and explain how you apply them in different scenarios. Provide examples of the evaluation techniques you employed in past projects.

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How do you approach feature selection for your models?

Explain the process of determining the most relevant features for a model, discussing techniques like correlation analysis, recursive feature elimination, and any tools or libraries you’ve used to aid in the selection process.

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Describe a challenging algorithm you implemented and the results achieved.

Share a specific example of a complex algorithm you developed, the problem it addressed, and its impact on the project’s success. Highlight the techniques and methodologies employed during the implementation.

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How do you ensure the robustness of your machine learning models?

Talk about strategies you use, such as cross-validation, regularization, and ensemble methods. Provide insights into how you monitor model performance over time and make necessary adjustments.

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What experience do you have working with large datasets?

Detail your experiences with managing, cleaning, and processing large datasets. Discuss any specialized tools or frameworks you've utilized to analyze big data, such as Spark, and how they facilitated your work.

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How do you stay up to date with advancements in machine learning?

Mention specific resources you follow, such as academic journals, blogs, podcasts, or conferences. Emphasize how you apply new knowledge to your work at adjoe or in personal projects.

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Explain a situation where you had to explain a complex machine learning concept to a non-technical audience.

Provide an example showcasing your ability to simplify complex topics effectively. Highlight how you communicated key concepts using analogies or visual aids to ensure understanding.

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Have you ever dealt with biased data? What steps did you take to mitigate it?

Discuss your experiences with biased datasets, your methods for identifying bias, and the corrective actions taken to adjust the model or data preprocessing techniques to ensure fairness.

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What are your thoughts on the future of machine learning in adtech?

Share your insights on emerging trends and technologies within machine learning, specifically relating to adtech. Discuss potential applications that can enhance user experience and advertising efficiency, showcasing your forward-thinking approach.

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DATE POSTED
November 29, 2024

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