• You will design, implement and optimize neural network architectures and deep learning models for various applications.
• You will develop and apply advanced mathematical models, including optimization techniques such as particle swarm optimization (PSO), genetic algorithms and other heuristic methods, to solve engineering and computational problems.
• You will lead and participate in research and development efforts in the areas of deep learning, artificial intelligence, and optimization algorithms.
• You will analyze large data sets to extract meaningful insights, trends, and patterns using machine learning techniques.
• You will work with subject matter experts and technical teams to integrate machine learning models into production systems.
• You will continuously improve model performance through experimentation, parameter tuning, and exploring new algorithms.
• You will keep up to date with the latest developments in AI, deep learning, and optimization algorithms, and propose new solutions to existing challenges.
• You will mentor younger data scientists and machine learning engineers within the team.
• You will develop and maintain technical documentation, including model architecture, implementation details, and performance reports.

• You have a master's degree in mathematics, computer science, engineering or a related field; a PhD is a plus.
• You have at least 2 years of professional experience in the industry in the areas of data science, machine learning or a related field, with a focus on neural networks, deep learning and optimization models.
• You are proficient in developing and training deep learning models using frameworks such as TensorFlow, PyTorch, Keras and others.
• You have strong mathematical skills, particularly in areas such as linear algebra, calculus, probability and optimization.
• You have practical experience with optimization algorithms, particularly particle swarm optimization (PSO), genetic algorithms, simulated annealing and other methods.
• You have a strong understanding of machine learning algorithms (supervised, unsupervised, and reinforcement learning) and practical experience applying these algorithms to solve real-world problems.
• You are familiar with data processing libraries such as NumPy and Pandas, as well as machine learning libraries such as scikit-learn and XGBoost.
• You have excellent communication and collaboration skills and work effectively in cross-functional teams.
• You pay close attention to detail and have the ability to manage multiple projects simultaneously.

Are you excited about the position but only meet 80% of the requirements? Apply anyway! We value your passion and motivation for the role more than perfection.

At pacemaker, we combine the innovative power of an agile SaaS start-up with the advantages and stability of an established corporate. We promote an open and collaborative working atmosphere in which we share our knowledge through cross-team collaboration and celebrate successes together.

• Remote-first culture: In addition to the freedom to work from anywhere in Germany, you can work from another EU country 20 days a year.
• Offices: If you're in the mood for office vibes, you can drop by our offices in Münster, Berlin or Düsseldorf at any time.
• Flexible working hours: Organize your working day according to your needs - without fixed core working hours, as long as it is compatible with your daily business & team.
• Team Days: Our monthly Team Days encourage interaction away from the daily routine, enable new employees to get to know the team and strengthen our corporate culture.
• Equipment: You work with a powerful MacBook that offers you optimal support in your daily work.
• Further training: Our Udemy Pro access gives you unlimited access to further training in your specialist area, allowing you to develop optimally in your field.
• Other benefits: thyssenkrupp pension scheme, bicycle leasing, corporate benefits and many other extras await you!

Does this sound like the right challenge for you? Then apply now via our career website and become part of our team: Apply for this position!

We look forward to receiving your application!