Data Scientist
Are you passionate about the potential of generative AI to transform industries and create innovative solutions? We are looking for talented data scientists to join our generative AI team. You will work on cutting-edge projects that leverage the latest advancements in AI to solve complex problems and drive business value.
What are you going to do?
As a member of the generative AI team, you will:
Develop and implement generative AI models to create new data, content, and solutions.
Collaborate with cross-functional teams to identify opportunities for applying generative AI in various business processes.
Conduct research to stay up-to-date with the latest advancements in generative AI and integrate them into our projects.
Optimize and fine-tune models to ensure high performance and accuracy.
Communicate findings and insights to stakeholders through presentations and reports.
Day-to-day activities include:
Designing and training generative models using techniques such as GANs, VAEs, and transformers.
Analyzing and preprocessing large datasets to prepare them for model training.
Experimenting with different architectures and hyperparameters to improve model performance.
Deploying models into production and monitoring their performance.
Collaborating with data engineers and software developers to integrate models into applications.
Profile:
Master’s or Ph. D. degree in Computer Science, Data Science, Machine Learning, or a related field.
At least 3-5 years of experience in a data science or machine learning role.
Strong programming skills in Python and experience with machine learning frameworks such as TensorFlow, PyTorch, or Keras.
Experience with generative models, including GANs, VAEs, and transformers.
Knowledge of deep learning techniques and neural network architectures.
Familiarity with cloud platforms such as AWS, Google Cloud, or Azure.
Excellent problem-solving skills and the ability to work independently and as part of a team.
Strong communication skills and the ability to explain complex concepts to non-technical stakeholders.
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