Generative AI Engineer - Remote - Freelance (12 months) - Hybrid
Location : Germany
Contract : 12 Months
Role Overview :
As a Generative AI Engineer, you'll play a pivotal role in advancing our AI capabilities by developing cutting-edge generative models. You'll work on projects that leverage AI for tasks such as text generation, image creation, and other innovative use cases. By collaborating with a dynamic team of engineers and researchers, you'll help drive the development of AI solutions that push the boundaries of what's possible, making a direct impact on our products and customers.
Key Responsibilities :
- Design, build, and deploy advanced generative models using cutting-edge frameworks like GPT, GANs, VAEs, and more.
- Train and fine-tune large models to ensure they meet high standards for performance and quality.
- Develop AI solutions across a range of applications, from text generation to image creation and other creative tasks.
- Research new techniques to continuously improve model efficiency, scalability, and overall performance.
- Work closely with teams across the company to integrate AI-driven solutions into our products.
- Optimize model performance with a focus on speed, resource efficiency, and scalability.
- Stay up-to-date with the latest developments in AI and machine learning.
Qualifications :
- Degree in Computer Science, AI, Machine Learning, or a related field (or equivalent experience).
- Strong hands-on experience in developing and deploying generative AI models (e.g., GPT, GANs, VAEs).
- Solid Python skills and familiarity with AI frameworks like TensorFlow, PyTorch, or JAX.
- Experience working with large datasets and distributed computing environments.
- In-depth understanding of machine learning algorithms, optimization, and model evaluation.
- A creative problem-solving mindset when it comes to AI applications.
- Strong communicator, able to explain complex technical concepts clearly to both technical and non-technical teams.
Preferred Skills :
- Experience deploying AI models in production.
- Familiarity with cloud platforms such as AWS, Google Cloud, or Azure.
- Knowledge of reinforcement learning, few-shot learning, and other advanced techniques.
- A strong commitment to AI ethics and a focus on building transparent, responsible AI solutions.