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Open nowFirst seen 16 hours ago

Generative AI Engineer

Talentport48 open roles

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Your applicationOpen nowGenerative AI EngineerTalentport

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The clock on this job

Early applications get read.

11.9% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.9%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: first seen 16 hours ago

The posting

Responsibilities

  • Research & Literature Survey - Investigate and analyze the latest research papers in Generative AI, LLMs, Computer Vision, Natural Language Processing, etc. - Monitor industry trends and assess applicability to our products - Leverage academic presentation experience for technology evaluation from scholarly perspectives
  • Model Development & Implementation - Design and develop state-of-the-art Generative AI models (GPT, Stable Diffusion, Custom Transformers, etc.) - Customize and structurally transform existing large language models - Implement using frameworks like PyTorch, TensorFlow, Hugging Face Transformers - Develop models across multiple modalities (image generation, speech recognition, text generation, etc.)
  • Performance Optimization - Optimize inference pipelines (reduce latency, improve throughput) - Apply optimization techniques (quantization, distillation, pruning) - Implement acceleration using GPU/TPU hardware - Ensure scalability and robustness for production environments
  • Evaluation & Verification - Build model performance evaluation frameworks - Analyze and improve issues (hallucinations, bias, output quality) - Conduct benchmark testing and drive continuous improvement cycles
  • Product Integration - Implement developed models as APIs and documentation for the product team use - Implement integration technologies (Vector DB, embeddings, RAG) - Build and operate AI systems on cloud platforms (GCP)

Required Qualifications

  • Academic & Foundational Knowledge - Master's or Ph.D. degree in Computer Science, Software Engineering, Artificial Intelligence, Machine Learning, Mathematics, Physics, or related fields - Deep knowledge/experience in the Generative AI domain
  • Technical Skills - Advanced Python programming: Practical experience with deep learning frameworks (PyTorch, TensorFlow, Hugging Face Transformers) - Deep learning fundamentals: Understanding of neural networks, Transformers, and attention mechanisms - Generative AI model implementation experience: Development/implementation experience with at least one Generative AI model (LLM, diffusion models, GANs, etc.)
  • Research & Implementation Experience - Design and implementation experience of algorithms based on the latest research papers in Computer Vision or Natural Language Processing - Research project experience with independent algorithm development and publication in academic conferences/journals - Experience applying research outcomes to actual products and achieving performance improvements
  • Problem-Solving Ability - Experience analyzing specific technical challenges in real projects and proposing/implementing concrete solutions - Ability to address complex technical problems with creative approaches
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