Auf einen Blick
- Aufgaben: Join our team to innovate machine learning solutions for ad systems and enhance model deployment.
- Arbeitgeber: Kayzen empowers mobile marketing teams with a transparent and controlled programmatic advertising platform.
- Mitarbeitervorteile: Enjoy flexible remote work, a $500 home-office budget, and a $1000 annual learning budget.
- Warum dieser Job: Be part of a dynamic team revolutionizing AdTech while growing your skills in a collaborative environment.
- Gewünschte Qualifikationen: 5+ years in deploying big data models, proficiency in Python, SQL, and machine learning frameworks required.
- Andere Informationen: Work with a multinational team and gain direct experience with management.
Das voraussichtliche Gehalt liegt zwischen 48000 - 84000 € pro Jahr.
Remote Global
Hello, I am Adriano, Machine Learning Lead at Kayzen, and I am now looking for a Machine Learning Engineer who will be a part of the machine learning engineering team bridging the gap between machine learning and ad systems engineering team.
But wait, you have not heard of Kayzen before?
Kayzen powers the world’s best mobile marketing teams to take programmatic advertising in-house. Built on the three key pillars of performance, transparency, and control, Kayzen is a DSP which enables leading app developers, agencies, media buyers, and D2C brands to run programmatic user acquisition, retargeting, and branding campaigns in self-serve or managed service mode.
With an unprecedented scale of >160bn daily ad requests from 2bn+ unique users worldwide, we serve more than 500M ads per day to 180 countries. Kayzen is accessible through our APIs or user interface.
The role
Are you a problem-solver, passionate about pushing the boundaries of machine learning in production? Do you thrive in a collaborative environment where you can both lead and be led , contributing your expertise while learning from others?
At Kayzen, we\’re revolutionizing the AdTech space with machine learning, and we\’re looking for a dedicated and proactive Senior Machine Learning Engineer to join our team. If you love the Machine learning craft and want to help us build a world-class ML infrastructure and processes, we want to hear from you!
Day to day
As a Senior Machine Learning Engineer, you\’ll be a key member of the Machine Learning Engineering team, bridging the gap between data science and ad systems engineering. You\’ll tackle the challenge of creating innovative solutions for petabyte-scale data models. Your work will span a wide range, from developing libraries and infrastructure to accelerate experimentation and deploying hundreds of models, to researching cutting-edge technologies.
- Accelerate Experimentation and Deployment : Create solutions to streamline our model experimentation and deployment processes.
- Robust Model Monitoring : Maintain and enhance our model monitoring capabilities to ensure optimal performance in production.
- Collaborate with Data Scientists : Partner with data scientists to develop new models, research novel methods, and create the best models for each use case within our AdTech platform.
- Productionalize Pipelines : Develop and productionalize model creation pipelines for our ML models in both bare-metal and cloud environments.
- Drive Innovation : Propose and lead projects to continuously improve our machine learning capabilities.
- Team Player : Contribute to a culture of continuous learning and improvement within the team.
- Champion Software Engineering Best Practices : Promote and implement software engineering best practices (version control, code review, testing, CI/CD) to ensure the reliability, maintainability, and scalability of our machine learning systems.
- Experienced Practitioner : 5+ years of proven professional experience in deploying big data-based models from conceptualization to deployment, ensuring sustained performance in production. Experience with ML tools (AWS Sagemaker, AIM, Catboost, VW, Redash, etc).
- Machine Learning Mastery : Proven experience with Machine Learning techniques (Neural Networks, Random Forest, etc.) and ML frameworks (Catboost, Mlflow, PyTorch, Tensorflow, etc.).
- Programming Proficiency : Fluency in relevant programming languages (Python, Java, etc.).
- Data Expertise : Strong proficiency in SQL & NoSQL and big data processing pipelines (we use Python, Spark, Airflow).
- Quantitative Background : Bachelor\’s/Master\’s degree in Mathematics, Physics, Computer Science, Machine Learning Engineering or a related field.
- Data Enthusiast : A genuine passion for working with data and uncovering insights.
- Problem Solver : Strong analytical and problem-solving skills to tackle complex challenges.
- Business Acumen : Ability to translate business requirements into solutions.
- Effective Communication : Excellent stakeholder management and communication skills.
Nice to have:
- Deep Learning Experience: Familiarity with deep learning techniques and applications.
- Clickhouse & AdTech: Prior experience with Clickhouse and/or the ad-tech industry.
- Real-Time Processing: Experience with real-time big data processing.
What do we offer?
- Exceptional career growth and learning opportunity.
- A unique opportunity to be part of an experienced team of industry experts and entrepreneurs who bring massive change to the Adtech market.
- Direct, day-to-day work experience with the management.
- A fun, driven, and multinational team located across Germany, India, Argentina, Ukraine, Turkey, the UK, and soon more countries.
- A flexible work-from-home arrangement.
- A 500-dollar home-office setup budget.
- A 1000-dollar annual learning and development budget.
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Machine Learning Engineer (m/f/d) Arbeitgeber: Kayzen

Kontaktperson:
Kayzen HR Team
StudySmarter Bewerbungstipps 🤫
So bekommst du den Job: Machine Learning Engineer (m/f/d)
✨Tip Number 1
Familiarize yourself with the specific machine learning tools mentioned in the job description, such as AWS Sagemaker and Catboost. Having hands-on experience or projects that showcase your proficiency with these tools can set you apart from other candidates.
✨Tip Number 2
Highlight any collaborative projects you've worked on, especially those involving data scientists or cross-functional teams. This role emphasizes teamwork, so demonstrating your ability to work well with others will be crucial.
✨Tip Number 3
Prepare to discuss your experience with big data processing pipelines and real-time data processing. Be ready to share specific examples of how you've tackled challenges in these areas, as they are key components of the role.
✨Tip Number 4
Showcase your problem-solving skills by discussing past projects where you had to innovate or improve existing processes. This will demonstrate your proactive approach and fit for a role that drives innovation in machine learning.
Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: Machine Learning Engineer (m/f/d)
Tipps für deine Bewerbung 🫡
Tailor Your Resume: Make sure to customize your resume to highlight your experience with machine learning, big data models, and relevant programming languages like Python and SQL. Emphasize your problem-solving skills and any specific projects that align with the job description.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for machine learning and your ability to work collaboratively in a team. Mention specific experiences where you have successfully deployed ML models or contributed to innovative solutions in previous roles.
Showcase Relevant Projects: Include links to any relevant projects or GitHub repositories that demonstrate your expertise in machine learning frameworks and tools. Highlight your experience with model monitoring, productionalizing pipelines, and any deep learning techniques you've used.
Prepare for Technical Questions: Be ready to discuss your technical skills in detail during the application process. Prepare examples of how you've tackled complex challenges in machine learning and be familiar with the latest technologies and methodologies in the field.
Wie du dich auf ein Vorstellungsgespräch bei Kayzen vorbereitest
✨Showcase Your Problem-Solving Skills
Be prepared to discuss specific challenges you've faced in machine learning projects and how you overcame them. Highlight your analytical thinking and problem-solving abilities, as these are crucial for the role.
✨Demonstrate Your Technical Proficiency
Make sure to brush up on your knowledge of relevant programming languages like Python and Java, as well as ML frameworks such as TensorFlow and PyTorch. Be ready to answer technical questions or even solve coding problems during the interview.
✨Emphasize Collaboration Experience
Since the role involves working closely with data scientists and other team members, share examples of successful collaborations from your past experiences. Discuss how you contributed to team projects and what you learned from others.
✨Prepare for Questions on Model Deployment
Expect questions about your experience with deploying machine learning models, especially in big data contexts. Be ready to explain your approach to model monitoring and productionalizing pipelines, as these are key responsibilities of the position.