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Data Scientist (Generative AI Experience)

SavageOne Pty Ltd

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In loco
ZAR 600.000 - 800.000
30+ giorni fa
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Data Scientist (Generative AI Experience)
SavageOne Pty Ltd
Johannesburg
In loco
ZAR 600.000 - 800.000
Tempo pieno
30+ giorni fa

Descrizione del lavoro

A leading technology firm in Johannesburg is seeking a talented Data Scientist specializing in Generative AI to design, build, and deploy next-generation models across text, image, and video applications. The ideal candidate will have a Bachelor's or Master's degree in a related field, proven experience with generative models, and proficiency in Python. Strong problem-solving and communication skills are essential. This role offers an innovative environment at the forefront of AI technology.

Competenze

  • Proven experience with generative models like GPT and Stable Diffusion.
  • Hands-on experience with large-scale data processing tools like Spark.
  • Excellent communication and collaboration skills.

Mansioni

  • Design and deploy generative models for diverse applications.
  • Collaborate with teams to integrate AI capabilities.
  • Ensure responsible deployment of AI systems.

Conoscenze

Generative models expertise
Proficiency in Python
Deep learning knowledge
Strong problem-solving skills
Cloud platform experience

Formazione

Bachelor's or Master's degree in Computer Science, Data Science, or AI

Strumenti

PyTorch
TensorFlow
AWS
Descrizione del lavoro
Data Scientist (Generative AI Experience)
About the job Data Scientist (Generative AI Experience)

Job Summary
We are looking for a talented and innovative Data Scientist specializing in Generative AI to join our team. In this role, you will design, build, and deploy next-generation generative models across text, image, and video applications. Youll work at the forefront of AI, harnessing cutting-edge technologies like transformers, diffusion models, and GANs to develop impactful solutions. This is a hands-on, research-driven role where your contributions will directly influence product innovation and user experience.

Key Responsibilities

Design, train, and deploy generative models including GANs, VAEs, Diffusion Models, and Transformers.

Build scalable AI solutions for content generation across text, images, and video.

Optimize model performance, latency, and inference efficiency for production use.

Collaborate with engineering, product, and design teams to integrate AI capabilities into core products.

Conduct research on the latest Generative AI methodologies and apply findings to enhance model performance.

Ensure the responsible development and deployment of AI, incorporating ethical practices and bias mitigation.

Manage large-scale datasets: data acquisition, preprocessing, augmentation, and quality control.

Develop robust APIs and machine learning pipelines to operationalize AI models.

Present technical findings and strategic insights to internal stakeholders and leadership.

Required Qualifications

Bachelor's or Masters degree in Computer Science, Data Science, Artificial Intelligence, or a related discipline.

Proven experience with generative models such as GPT, Stable Diffusion, StyleGAN, or similar.

Proficient in Python and experienced with ML frameworks (PyTorch, TensorFlow, or JAX).

Solid understanding of deep learning, NLP, computer vision, or multimodal AI systems.

Experience with cloud platforms (AWS, Azure, GCP) and MLOps best practices.

Hands-on experience with large-scale data processing tools (Spark, Dask, or similar).

Strong problem-solving ability and a research-oriented mindset.

Excellent collaboration and communication skills.

Preferred Qualifications

Experience fine-tuning LLMs and working with retrieval-augmented generation (RAG) architectures.

Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate).

Understanding of responsible AI principles and experience applying fairness or bias mitigation techniques.

Contributions to academic publications or open-source projects in the field of Generative AI.

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* Il benchmark retributivo si basa sugli obiettivi retributivi dei leader del mercato nei rispettivi settori. È pensato per orientare gli utenti Premium nella valutazione delle posizioni aperte e aiutarli a negoziare la propria retribuzione. Tale benchmark non è fornito direttamente dall'azienda, quindi la retribuzione effettiva potrà risultare anche notevolmente superiore o inferiore.

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