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Generative AI Engineer

Location: Frankfurt am Main, Germany

Responsibilities

 

  • Research, develop, and implement generative models such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Transformers for various applications including image generation, text generation, and creative content synthesis.

  • Design and optimize neural network architectures and training pipelines to achieve high-quality and diverse outputs while addressing challenges such as mode collapse, training stability, and scalability.

  • Collect, preprocess, and curate large-scale datasets for training and evaluating generative models, ensuring data quality, diversity, and relevance to specific use cases.

  • Collaborate with cross-functional teams to define project goals, experiment design, success metrics, and evaluation methodologies for generative AI projects.

  • Stay current with the latest research papers, techniques, and advancements in generative AI and contribute to the internal knowledge sharing and continuous learning initiatives.

  • Work closely with product teams to integrate generative AI capabilities into existing products or develop new products and features that leverage generative models.

  • Collaborate with external research partners, academic institutions, and industry experts to advance the field of generative AI through collaborative research projects and publications.

Qualifications

 

  • Master's or Ph.D. degree in Computer Science, Electrical Engineering, Mathematics, or related field, with a focus on machine learning, deep learning, or artificial intelligence.

  • Proven experience in developing and deploying generative models, with a strong track record of research publications, projects, or applications in the field of generative AI.

  • Proficiency in deep learning frameworks such as TensorFlow, PyTorch, or JAX, and experience with training and fine-tuning large-scale neural networks.

  • Strong understanding of generative model architectures, loss functions, regularization techniques, and optimization algorithms.

  • Experience with advanced topics in deep learning such as unsupervised learning, self-supervised learning, and reinforcement learning is a plus.

  • Familiarity with cloud computing platforms (e.g., AWS, Azure, Google Cloud Platform) and distributed computing frameworks for scalable model training and deployment.

  • Excellent programming skills in languages such as Python, with experience in data manipulation, visualization, and analysis libraries (e.g., NumPy, Pandas, Matplotlib).

  • Proficiency in using deep learning development tools and libraries for model development, debugging, and experimentation.

  • Familiarity with version control systems (e.g., Git), collaborative software development workflows, and agile methodologies.

  • Strong analytical and problem-solving skills, with the ability to experiment, iterate, and troubleshoot effectively in a research-oriented environment.

  • Excellent communication and collaboration skills, with the ability to work effectively in a multidisciplinary team and communicate complex technical concepts to non-technical stakeholders.

  • Fluent English skills necessary, German preferred

​Benefits

  • Competitive salary and performance-based incentives

  • Opportunities for professional development and training

  • Collaborative and innovative work environment

  • Exposure to a diverse range of industries and projects

  • Flexible work arrangements

  • Chance to be part of a growth story

If you are passionate about using data to drive business success and enjoy working in a dynamic and collaborative environment, we would like to hear from you.

How to Apply

 

Please submit your resume and transcripts to careers@analytixone.com.

ANALYTIX ONE is an equal opportunity employer. We encourage applications from candidates of all backgrounds and experiences.

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