Generative AI Engineer
Location: Frankfurt am Main, Germany
Responsibilities
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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.
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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.
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Collect, preprocess, and curate large-scale datasets for training and evaluating generative models, ensuring data quality, diversity, and relevance to specific use cases.
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Collaborate with cross-functional teams to define project goals, experiment design, success metrics, and evaluation methodologies for generative AI projects.
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Stay current with the latest research papers, techniques, and advancements in generative AI and contribute to the internal knowledge sharing and continuous learning initiatives.
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Work closely with product teams to integrate generative AI capabilities into existing products or develop new products and features that leverage generative models.
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Collaborate with external research partners, academic institutions, and industry experts to advance the field of generative AI through collaborative research projects and publications.
Qualifications
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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.
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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.
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Proficiency in deep learning frameworks such as TensorFlow, PyTorch, or JAX, and experience with training and fine-tuning large-scale neural networks.
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Strong understanding of generative model architectures, loss functions, regularization techniques, and optimization algorithms.
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Experience with advanced topics in deep learning such as unsupervised learning, self-supervised learning, and reinforcement learning is a plus.
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Familiarity with cloud computing platforms (e.g., AWS, Azure, Google Cloud Platform) and distributed computing frameworks for scalable model training and deployment.
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Excellent programming skills in languages such as Python, with experience in data manipulation, visualization, and analysis libraries (e.g., NumPy, Pandas, Matplotlib).
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Proficiency in using deep learning development tools and libraries for model development, debugging, and experimentation.
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Familiarity with version control systems (e.g., Git), collaborative software development workflows, and agile methodologies.
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Strong analytical and problem-solving skills, with the ability to experiment, iterate, and troubleshoot effectively in a research-oriented environment.
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Excellent communication and collaboration skills, with the ability to work effectively in a multidisciplinary team and communicate complex technical concepts to non-technical stakeholders.
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Fluent English skills necessary, German preferred
​Benefits
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Competitive salary and performance-based incentives
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Opportunities for professional development and training
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Collaborative and innovative work environment
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Exposure to a diverse range of industries and projects
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Flexible work arrangements
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Chance to be part of a growth story
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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.
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How to Apply
Please submit your resume and transcripts to careers@analytixone.com.
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ANALYTIX ONE is an equal opportunity employer. We encourage applications from candidates of all backgrounds and experiences.